Available Deep Research Agents: A Comparison

Overview

AI-powered deep research tools continue to advance rapidly, with stronger agent autonomy, improved verification systems, and tighter integration into professional workflows. This report tracks leading consumer-accessible and developer-integrated platforms, focusing on accuracy, depth, breadth, and accessibility as of June 2026. Freely or OAuth-accessible leaders include Perplexity AI, OpenAI ChatGPT (GPT-5.3/5.4), Claude 4 Opus/Sonnet, Google Gemini 2.5 Pro, DeepSeek, x.ai Grok 4.2, and Zhipu GLM-4.5, each differentiating in evidence handling, multimodal reasoning, and orchestration capabilities.

Recent Developments (June 2026)

Model Capability Advancements:

• OpenAI GPT-5.3/5.4 shows continued gains in long-horizon task reliability, with more stable multi-agent coordination, improved memory persistence across sessions, and stronger alignment between intermediate reasoning and cited evidence.

• Claude 4 Opus/Sonnet improves calibrated reasoning and controllability, with clearer uncertainty signaling and more consistent behavior in extended, document-heavy workflows.

• Google Gemini 2.5 Pro maintains leadership in multimodal research, with enhanced cross-modal retrieval and grounding and expanded collaborative verification features in shared workspaces.

• Cross-vendor trend: auditable research pipelines are now standard, including step-level citations, replayable execution traces, structured research logs, and exportable evidence graphs. Persistent memory and context layering are increasingly integrated into research agents.

Platform-Specific Updates:

• Perplexity AI: Academic Mode expands citation graph traversal, contradiction detection, and source clustering, with improved trust scoring and team-based evaluation workflows.

• ChatGPT (GPT-5.3/5.4): Operator agents improve parallel execution, task persistence, and recovery, with broader enterprise integrations and more standardized research log exports.

• Claude 4 Opus/Sonnet: Gains stronger session continuity, checkpointing, and tool transparency, improving reliability in long-running analytical tasks.

• Gemini 2.5 Pro: Advances interactive research workspaces, enabling tighter linking between claims, sources, and multimodal artifacts, with growing adoption in collaborative environments.

• Grok 4.2 (x.ai): Strengthens real-time intelligence, with faster ingestion of live data streams and improved synthesis of emerging global trends.

• DeepSeek R1: Continues momentum in open-weight ecosystems, with improved reproducibility tooling and growing enterprise adoption of hybrid deployments.

• Zhipu GLM-4.5: Expands multilingual and cross-domain reasoning, with improved English academic synthesis and increased usage across Asia-Pacific enterprises.

Key Competitors in Research AI (June 2026):

• Perplexity AI, Claude 4 Opus/Sonnet, and Gemini 2.5 Pro lead in structured, citation-rich research workflows.
• ChatGPT (GPT-5.3/5.4) with Deep Research + Operator leads in agentic, multi-step autonomous inquiry.
• DeepSeek and Grok emphasize openness, transparency, and real-time data integration.
• GLM-4.5 (Zhipu) continues expanding multilingual and cross-region research capabilities.

Market Dynamics (June 2026)

The ecosystem shows increasing standardization alongside differentiation in execution quality:

• Pricing: Stable at ~$20/month standard tiers, with $150–$200/month premium tiers for higher compute, longer context, and agent-heavy workflows.
• Source Verification: Provenance chains, citation graphs, and confidence scoring are baseline; Perplexity and Gemini remain leaders in user-facing transparency.
• Multimodal Research: Fully integrated across major platforms; Gemini retains an edge in large-context multimodal alignment.
• Reasoning Transparency: OpenAI and DeepSeek emphasize traceability and replayability; Anthropic focuses on interpretability and uncertainty calibration.
• Autonomous Research Adoption: Expands to ~60–75% of professional users piloting or deploying agentic workflows, especially in analytics, compliance, and R&D.
• Open Source Growth: DeepSeek ecosystem accelerates open/closed hybrid deployments with enterprise-grade tooling.
• Integration: Deeper embedding across Google Workspace, Microsoft 365, Notion, Slack, and internal knowledge systems supports coordinated multi-agent workflows.
• Regulation Impact: EU AI Act enforcement Phases shape product design, requiring auditability, logging, risk classification, and tighter data governance for research systems.

Emerging Trends to Watch

1. Domain-Specific Agents: Expansion in regulated industries with tighter coupling to proprietary datasets and compliance constraints.
2. Citation Intelligence: Interactive, queryable evidence graphs with trust scoring, contradiction detection, and lineage tracking.
3. Collaborative Research Systems: Multi-user, multi-agent environments with shared reasoning layers and live co-analysis.
4. Reproducibility Standards: Audit trails, dataset versioning, and replayable research logs becoming enterprise defaults.
5. Agent Orchestration: Coordinated multi-agent systems handling parallel research tasks with centralized control layers.
6. Real-Time + Historical Fusion: Blending live data streams with archival reasoning for continuous intelligence workflows.
7. Privacy-Preserving AI: Growth in on-premise, federated, and encrypted inference, driven by regulatory pressure and enterprise adoption.
8. Persistent Research Memory: Systems retaining structured knowledge across sessions, enabling cumulative, longitudinal research workflows.

Perplexity AI

Perplexity AI remains a citation-first research and answer engine with tiered offerings (Pro, Max, Enterprise Pro, Enterprise Max) designed for deep, multi-step research, real-time source verification, and agentic workflows. The research stack emphasizes inline citations, source previews, refreshed deep-research tooling, sandboxed execution, and a public-facing Search API that leverages the same scalable infrastructure.

Key Capabilities:

• Deep Research: The Deep Research workflow continues to advance, with ongoing experiments across model families and orchestration scaffolds to optimize reasoning and export capabilities. In 2026, Perplexity expanded rollout of enhanced reasoning workflows, enabling faster synthesis and broader export options for complex inquiries.[4][5][6][10]
• Source Discovery: The Search API provides access to a massive index of webpages with refined retrieval and real-time result streaming, plus domain-specific filtering enhancements. The system maintains high update velocity to ensure freshness.[2][5][9][10]
• Multimodel Workflow: The routed model stack now includes newer frontier models and expanded handoff capabilities for multi-step tasks, improving interoperability between components such as Computer, Comet Agent, and external models. GPT-5.5 and related frontier models are available through plan- and task-based routing.[7][8]
• Team and Enterprise Workspaces: Enterprise offers stronger admin controls, org-level credit visibility, memory features, and access to licensed datasets for finance teams; Enterprise Max adds broader browsing and file capabilities, with governance tooling for policy enforcement and audit trails.[8][9][10]
• Academic and Research Use: Live-web research with citations and app connectors remains central, with expanded support for email, calendars, knowledge bases, and project tools; collaboration features and shared workspaces support concurrent researchers.[10][8]

Pricing (as of 2026-06-24):

• Free tier: Basic queries with limited search; no advanced deep-research or Computer features.
• Pro: $20/month, includes access to advanced research features and generous usage limits for typical users.
• Max: $200/month, includes unlimited Labs usage and access to advanced research and Computer features.
• Enterprise Pro: $40/seat/month, includes centralized billing, team collaboration, security controls, and enterprise knowledge-base integrations.[10]
• Enterprise Max: $325/seat/month, includes unlimited Labs queries, expanded security and analytics, and broader premium model access.[10]

Best For:

Academic and technical research, legal synthesis, live-source fact-checking, and team workflows combining research, browsing, file access, and connected apps. Particularly useful for users who require grounded, cited answers and organizations needing enterprise AI research controls.[2][7][8][10]

Limitations:

• Some advanced capabilities (e.g., Comet Max Assistant, unlimited Labs, newest Computer features) remain tier-gated to higher plans.[8]
• Free and Pro tiers impose usage caps and feature gating for compute-intensive tasks.[10]
• Public materials provide partial visibility into routing logic and internal model orchestration.[1][7]

Technical Specifications:

• Model stack: Routing across frontier models including GPT-5.5, Claude Sonnet 4.6, and Claude Opus 4.6 depending on plan and task.[1][7][8]
• Search infrastructure: Global index of hundreds of billions of webpages with fine-grained segmentation, hybrid retrieval, and rapid index updates.[5][2]
• API: Developer platform features include Search API, Agent API, Embeddings API, and Sandbox API, with roadmap items for lower latency, video/file support, async webhooks, and improved context handling. Real-time result streaming and richer citation metadata continue to improve.[3][8]

ChatGPT (OpenAI)

ChatGPT, powered by GPT‑5.4 and GPT‑5.2, now emphasizes a three-mode system in ChatGPT—Instant, Thinking, and Pro—with GPT‑5.4 Thinking positioned as the most capable reasoning model for difficult, real-world work.[2][10]

Key Capabilities:

• GPT‑5.x Reasoning: GPT‑5.4 Thinking is optimized for complex reasoning, document understanding, image understanding, tool use, and research tasks that combine many web sources; GPT‑5.2 also introduced improved reasoning and higher quality across ChatGPT and the API.[10][2]
• Web Browsing: Real-time research workflows in ChatGPT combine web search, multi-source synthesis, and iterative refinement for difficult questions.[2]
• Code Generation: GPT‑5.4 is stronger at spreadsheet creation and editing, polished frontend code, slideshow creation, hard math, and instruction following, making it more useful for technical and business workflows.[2]
• Agentic Workflows: ChatGPT supports deeper tool use and research-style tasks, with model routing between Instant and Thinking to balance speed and depth.[2]
• Document Analysis: ChatGPT can work across documents and images, and GPT‑5.4 is explicitly optimized for document understanding and image understanding.[2]
• Canvas: Canvas remains part of the ChatGPT experience, but Pro does not include Canvas, Apps, Memory, or image generation.[2]

Pricing:

• Free: Limited access to ChatGPT with GPT‑5.3 Instant and constrained usage.
• Go: Lower-cost paid access with increased limits.
• Plus: Access to GPT‑5.3 Instant and GPT‑5.4 Thinking, with broader usage limits.
• Pro: GPT‑5.4 Pro for research-grade intelligence; available to Pro, Business, Enterprise, and Edu plans.[2]

Best For: Complex research, advanced reasoning, coding, document-heavy workflows, and users who want stronger model routing between fast and deep responses.[10][2]

Technical Specifications:

• Models: GPT‑5.3 Instant, GPT‑5.4 Thinking, and GPT‑5.4 Pro are the current ChatGPT model modes; GPT‑5.2 is also available in ChatGPT and the API.[10][2]
• Integration: ChatGPT remains deeply tied into the OpenAI product stack and Microsoft ecosystem, including Azure-based enterprise deployment patterns and Teams-style integrations built on Azure OpenAI.[1][5]
• Multimodal: ChatGPT supports text, image, and document understanding, with GPT‑5.4 explicitly improved for image and document tasks.[2]

Unique Strengths:

• Model routing that automatically shifts from fast responses to deeper reasoning when needed.[2]
• Stronger research and synthesis performance than earlier generations, especially for complex, multi-source tasks.[2]
• Broad enterprise deployment options through Azure OpenAI and Microsoft-connected workflows.[5][1]
• Publicly documented security posture for business products and API deployments includes SOC 2 Type II compliance claims in 2026 coverage.[7]

Note: Updates reflect ongoing enhancements through mid-2026, with continued emphasis on scalable enterprise deployment, enhanced multimodal capabilities, and strengthened governance and security posture across OpenAI’s product suite. OpenAI’s enterprise and Azure OpenAI integration continue to evolve, with data-zone features and EU/US data residency options expanding capacity and resilience for large-scale deployments.[9][1][5][10]

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Claude.ai (Anthropic)

Claude Opus 4.7 is now Anthropic's flagship Claude model, with Opus 4.6 still widely referenced as the prior generation and Sonnet 4.6 remaining the current mid-tier workhorse; there is still no publicly confirmed Sonnet 4.7 release as of May 2026. Opus 4.7 is generally available across claude.ai, the Claude API, and major cloud platforms (Amazon Bedrock, Google Vertex AI, Microsoft Foundry), and it emphasizes stronger agentic coding, stricter instruction following, higher-resolution vision (3×+ image resolution), and more reliable long-running workflows than Opus 4.6.

Key Capabilities:

• Claude Opus 4.7 / 4.6 / Sonnet 4.6: Opus 4.7 improves on Opus 4.6 in advanced software engineering, long-running tasks, self-verification, and high-resolution vision; Anthropic says it is better at complex async workflows, more precise about instructions, and shows reduced hallucinations and reward hacking. Opus 4.6 remains a major step up from earlier Claude 4 models for planning, debugging, finance, research, and codebase navigation.

• Research Mode: Multi-step web research with source synthesis, inline citations, and tighter integration with external tools remains a core Claude workflow, especially for knowledge work and agentic research tasks.

• Agent Teams: Claude Code's agent teams officially launched February 6, 2026 alongside Opus 4.6 as a research preview, letting multiple agents work in parallel on decomposable tasks with isolated context windows, shared task lists, and peer-to-peer messaging; the team lead coordinates, teammates work independently, and it supports split-pane mode via tmux/iTerm2.

• Computer Use: Desktop and browser automation remain supervised but more reliable, with better long-horizon execution, improved error recovery, and stronger code-review/debugging behavior in the newest Opus models.

• Extended Context: 1M-token context is available in beta for Opus 4.6 and Opus 4.7 on the Claude Developer Platform; Anthropic reports materially better long-context retrieval and less drift on needle-in-a-haystack tasks than prior Claude models.

• Artifacts and Office Work: Claude continues to produce structured outputs such as code, notebooks, presentations, and documents, with stronger support for Excel and PowerPoint; as of March 2026, Claude for Excel and PowerPoint share full conversation context across open files, and Skills (repeatable workflows) are available in both add-ins on all paid plans for Mac/Windows.

• Tool Use / Function Calling: Native tool orchestration, adaptive thinking, and context compaction are now central platform features, with Opus 4.7 adding xhigh effort control and task budgets in public beta.

• MCP Apps: Interactive MCP Apps are now an official Claude feature, allowing apps with rich UIs to render directly in chat for partners such as Asana, Slack, Figma, Box, Canva, Amplitude, and others.

Pricing:

• Free: Claude 3.5 Sonnet remains the baseline free-tier reference in older summaries, but the current product emphasis is on Claude 4-era models and feature gating; free-tier limits remain strict.

• Pro: Roughly $20/month, with higher usage caps and access to premium Claude features, depending on rollout and region.

• Max: Higher-usage consumer tier with priority access to newer Claude capabilities and longer context/features, pricing varying by usage level and plan.

• Team/Enterprise: Work-oriented plans continue to focus on shared workspaces, admin controls, and enterprise integrations; Anthropic's broader rollout includes Claude in Excel and PowerPoint plus org-scale deployments like KPMG; Excel/PowerPoint add-ins with shared context and Skills are available on all paid plans.

• API: Opus 4.6 and Opus 4.7 are priced at $5/M input and $25/M output tokens; Opus 4.6 adds premium pricing above 200k-token prompts on the Claude Platform, while Opus 4.7 keeps the same headline pricing and introduces additional effort controls.

Best For: Large-scale document and code analysis, agentic workflows, research synthesis with citations, desktop automation via Computer Use, and collaborative multi-agent setups. Opus 4.7 is especially strong for harder coding, long-horizon execution, visually rich professional outputs, and advanced document analysis.

Limitations:

• Computer Use still requires supervision and careful environment setup, especially on complex or brittle UIs.
• 1M context is still beta on the API side and remains concentrated in paid/platform tiers.
• Opus 4.7's stronger instruction following means older prompts and harnesses may need retuning to avoid unexpected literal behavior.
• Usage caps and feature access still vary substantially by plan, and not all advanced capabilities are fully generalized across tiers.
• Agent teams remain experimental with known limitations (no session resumption, no nested teams).

Technical Specifications:

• Models: Claude Opus 4.7; Claude Opus 4.6; Claude Sonnet 4.6; Claude Haiku 4.5.

• Context: Up to 1M tokens in beta for Opus 4.6 and 4.7; standard tiers remain lower, with 200k still common in older plan references.

• Multimodal: Text and images, with Opus 4.7 supporting 3×+ higher-resolution images and stronger document/diagram interpretation.

• Tooling: Native tool use/function calling, adaptive thinking, context compaction, task budgets, and MCP Apps with interactive UI.

• Safety: Constitutional AI remains the foundation, with stronger safeguards around cyber misuse in the latest Opus release; Opus 4.7 shows minimal misaligned behavior risk, similar to Opus 4.6, with greater honesty and reduced critical omissions.

• Computer Use: Browser and desktop automation continue to improve, especially for code review, research, and multi-step workflows.

Unique Strengths:

• Mature agent tooling across research, tool use, and multi-agent execution in one ecosystem.
• Stronger long-context performance that Anthropic positions as meaningfully better than prior Claude generations.
• Official multi-agent coordination via agent teams in Claude Code (shipped Feb 2026) with isolated contexts and team protocols.
• Deeper enterprise integration, including shared-context Excel/PowerPoint add-ins with Skills and interactive MCP apps inside chat.
• Better high-resolution vision (3×+), stronger self-checking on hard coding/reasoning, and reduced hallucinations in Opus 4.7.

Google Gemini Deep Research

Gemini Deep Research remains anchored in Gemini 3.1 Pro, supplemented by the latest deep-research-preview and max-preview iterations as of 2026-06, with ongoing expansion across Google Search, Scholar, Maps, Workspace, and enhanced agentic tooling for end-to-end research workflows.[1][2][3]

Key Capabilities:

• Gemini 3.1 Pro Reasoning: Maintains PhD-level reasoning for complex tasks including math, science, logic, multi-step inference, agentic planning, code-based animations, and advanced system synthesis, with ongoing benchmarking across ARC-AGI-2, GPQA Diamond, SWE-Bench Verified, and BrowseCamp families.[2][4][6][9]
• Context Window: 1M-token input context for Deep Research previews via Vertex AI/API, with 65,536 output tokens; consumer Pro configurations optimize token usage; implicit caching remains active with a 4,096-token minimum for Gemini 3.1.[7][9][1]
• Ecosystem Integration: Full access to Google Search, Scholar, Maps, News, YouTube, Shopping, Flights, Workspace, Drive, Calendar, plus MCP servers, code execution, file search, Knowledge Graph, and Interactions API for agentic workflows, with stability improvements following May 2026 changes to outputs/roles and response_format controls.[6][10][1][2]
• Multimodal Mastery: Native handling of text, images (up to 6), audio (up to 180s without transcription), video (up to 120s), PDFs (up to 6 pages), and interleaved inputs via Gemini Embedding 2 for unified 3072-dim embeddings with flexible output sizes, cross-modal search, retrieval, clustering, and recommendations across 100+ languages.[3][7]
• Real-Time Data: Live integration of sports, markets, news, weather, and traffic with collaborative planning and native visualizations like charts.[9]
• Deep Research Agent: Autonomous multi-step research producing cited reports with expandable sections; supports collaborative plan refinement, external tools, and built-in tools like Google Search in Interactions API.[5][10][6]
• Workspace Integration: In-place analysis of Docs, Sheets, Drive files, with collaborative outputs and up-to-date enterprise data governance.[2]
• Video & Audio Analysis: Frame-level video analysis with direct audio embedding (no transcription required up to 180s), lecture summarization, and podcast-style report overviews.[7]

Pricing:

• Free tier: Core model access excluding Deep Research; baseline rate limits apply (5–15 RPM in certain tiers).[1]
• Advanced / Gemini Advanced: Approximately $20 USD/month for premium models, Deep Research access, 1M context, and expanded features; Workspace Business ($20/user/month), Enterprise ($30/user/month).[5]
• API tiers: Tier 1 (150–300 RPM with billing), Tier 2 ($250+ spend for 1,000 RPM), Tier 3 enterprise (custom up to 4,000+ RPM).[5]

Best For:

Google ecosystem users, researchers, technical teams requiring long-context multimodal synthesis, real-time data, Workspace collaboration, and enterprise-grade reporting.[2]

Limitations:

• 1M context suits most tasks but can add latency for very large inputs; Pro users may encounter 32k–64k token caps in some configurations.[7]
• Slower for complex agentic runs; requires source verification in regulated environments.[2]
• Less optimal for non-Google stacks or strict privacy requirements.
• Rate limits enforced via token bucket; exceeding triggers 429 errors with exponential backoff.[1]

Technical Specifications:

• Model: Gemini 3.1 Pro and updated previews (e.g., deep-research-preview-04-2026, deep-research-max-preview-04-2026) optimized for reasoning and agency with improved token efficiency and planning capabilities.[9][5][2]
• Context window: 1M input tokens via API/Vertex AI; multimodal inputs supported with mindful usage; implicit caching requires a minimum of 4,096 tokens for Gemini 3.1.[9][1]
• Multimodal: Text, images, audio, video, PDFs via Gemini Embedding 2 with interleaved inputs and unified vectors for cross-modal semantic similarity; supports 8192-token text context and multi-document ingestion.[3][7]
• Integration: Google Search ecosystem plus MCP, code execution, file search, Knowledge Graph, Interactions API (v1beta) with ongoing adjustments to outputs/roles, response_format controls, and task orchestration.[10][6][2]
• Video: Up to 120s MP4/MOV analysis with embeddings; support for PNG/JPEG images.[7]
• API: Gemini API/Vertex AI with rate limits (RPM/TPM/RPD/IPM) and implicit caching; Interactions API requires Gen AI 1.55.0+.[6][10][1]

Unique Strengths:

• Leading 1M consumer context support for codebases, videos, and multi-doc inputs via API/Vertex.[1]
• Scholar/Search depth with citations, Gemini Embedding 2 enabling agentic multimodal RAG, visual search, and cross-language capabilities across 100+ languages.[3][7]
• Advanced multimodal support including direct audio/docs (180s), interleaved inputs, and robust tool-use for complex multi-step tasks.[1][7]
• Workspace-native collaboration and enterprise pipelines; enhanced diagram generation and animated SVGs from prompts for code-based graphics.[9][2]

x.ai Grok

Grok's lineup now centers on Grok 4.20 and Grok 4.3, with Grok 4.3 listed as the current flagship for agentic tool use and configurable reasoning, and Grok 4.20 continuing as a major production/API variant featuring a 2M-token context window and multi-agent collaboration as a core differentiator.

Key Capabilities:

• Grok 4.3 (April 2026–): Flagship model emphasizing minimal hallucinations, strong instruction following, and enhanced multimodal capabilities. Context window 1M tokens (per docs) with configurable reasoning effort (none/low/medium/high, default low); supports non-reasoning mode and native video understanding, plus improved document-generation (PDFs, spreadsheets, presentations) and extended input modalities (text + image). Live on xAI API; voice interactions via integrated audio capabilities are available through the platform surfaces.
• Grok 4.20 (Feb–Mar 2026): Beta/production variant featuring native multi-agent collaboration with four specialized agents—Grok/Captain (coordinator), Harper (research & facts), Benjamin (math/code/logic), and Lucas (creative synthesis)—operating in parallel with internal debate and peer review before merging answers. Supports up to 16 agents on the Heavy tier, parallel reasoning, built-in web/X search, structured outputs, and a 2 million token context window.
• Real-Time Access: Grok can decide whether to search X public posts and the web, providing live information and signals.
• Reasoning: 4-agent parallel-debate architecture reduces hallucinations versus single-path reasoning; Grok 4.20 remains the clearest public example of parallel-debate inference.
• Multimodal: Text, voice, image, and video capabilities, including a Voice API and an Imagine API for image/video generation/editing; Grok 4.3 accepts text and image inputs with text output.
• Voice & Live Interaction: Voice API enables real-time conversations, speech-to-text, and text-to-speech with sub-second latency where available.
• "More Real" Modes: Some surfaces may display less-filtered responses; availability depends on subscription, region, and interface.

Pricing (2026):

• Basic: Free tier with limited usage (60 requests/minute, 45K tokens/minute, 60-second burst).
• SuperGrok (~$30/mo or $300/yr): Standard paid access with higher limits and premium features.
• SuperGrok Heavy (~$300/mo): Highest consumer tier offering early access to advanced models (including Grok 4.3 beta), higher limits, and significant multimedia generation capacity (video generation caps apply; quality can degrade beyond thresholds).
• API: Grok 4.3 typically priced at around $1.25 per 1M input tokens and $2.50 per 1M output tokens (with cache reads extra); Grok 4.20 priced higher on tokens; enterprise API with Zero Data Retention (ZDR) option available.

Best For: Real-time research, social/media intelligence, multimodal workflows, streaming analysis, coding/tool-use pipelines, and agent-style tasks leveraging live search and parallel reasoning.

Limitations:

• Heavy reliance on X-public data can bias coverage toward platform signals.
• Grok 4.3 context window is smaller than 4.20; ultra-long document workflows may favor 4.20.
• Premium access and enterprise controls require paid tiers; video capacities have caps in Heavy plans.
• Output quality varies by mode and configuration of tool usage and reasoning.

Technical Specifications:

• Models: Grok 4.20 and Grok 4.3; 4.3 is the current flagship with video and document-generation enhancements.
• Architecture: Multi-agent collaboration with parallel reasoning; 4 agents standard, up to 16 on Heavy; verification loops and tool-calling capabilities.
• Context window: 2M tokens for Grok 4.20; 1M tokens for Grok 4.3 (per current docs).
• Multimodal: Text, voice, image, and video support; Grok 4.3 accepts text and image inputs.
• Data integration: Live X public-post search plus web search integration.
• API: Tiered consumer and enterprise access; ZDR option for enterprise teams. Rate limits vary by subscription.

Unique Strengths:

• Tight real-time X integration for current-event and social-signal workflows.
• Native multi-agent reasoning with a clear agent stack and reduced hallucinations.
• Strong tool-calling and instruction-following in Grok 4.3, with configurable reasoning effort.
• Broad multimodal and voice support in a single product family.

DeepSeek

DeepSeek remains a leading force in technical-research and developer-focused AI, with R1-0528, the V3.2 family, and the V4 MoE series (Flash/Pro/Max tiers) excelling in code-heavy, math-intensive, and long-context agent workloads at scale.[1][5]

Key Capabilities:

• DeepSeek R1-0528: Open-weight reasoning model (2025) widely used for mathematical reasoning (AIME-level ≈87%), code generation/debugging (Aider ≈70%+), multi-step inference (GPQA ≈80%+), structured scientific pipelines, and transparent chain-of-thought with low hallucination.[1]
• API Adoption: Rapid 2026 growth with 6B+ monthly calls, >140M MAU; embedded in agent frameworks, IDEs, pipelines.[1]
• Cost Efficiency: 10–30× cheaper than closed models; V4-Flash for high-throughput (~$0.02–$0.03/M input cache hit), V4-Pro/Max for accuracy; ~90% caching discounts.[5][1]
• Technical Focus: Large-repo analysis, algorithmic reasoning, formal methods, vulnerability discovery, literature synthesis.[1]
• Open Source: Open weights for R1/V-series enable self-hosting, fine-tuning, air-gapped use; robust community tools.[1]
• General Models: V3.2/V4 hybrids improve agent reliability (SWE-bench Verified ≈65–70% V3.2; 80.6% V4-Pro-Max); configurable depth, tool coordination.[5][1]
• Coder Series: Strong in multi-language generation, debugging, test synthesis for dev tools.[1]
• Self-Hosting: Cloud API, on-prem, Kubernetes, GPU stacks with mixed-precision/sparse inference.[1]

Pricing (May 2026):

• Free tier: Web chat limits
• API:
  • V3.2: Input ~$0.12–$0.25/M, Output ~$0.25–$1.00/M
  • R1-0528: Input ~$0.50/M, Output ~$2.00/M
  • V4-Flash: ~$0.02–$0.03/M input (cache hit)
  • V4-Pro: Input $0.44/M, Output $0.87/M (1M context)[1]
  • V4 Max: ~$0.12–$0.20/M[5][1]

Best For: Technical researchers, developers, cost-sensitive APIs, agents, self-hosted/privacy-focused deployments.

Limitations:

• Less polished UI vs. U.S. platforms
• Lagging RAG/citations/enterprise integrations
• Weaker creative/media tasks vs. multimodal leaders
• We are seeing maturing enterprise support (SLAs/services); high hallucination (94% on unknown tasks)[5][1]

Technical Specifications:

• Models: R1-0528, V3.2, Coder, V4 MoE (V4-Pro: 1.6T total params, 49B active/token)[1]
• Context: V3.2 128K–164K; V4 up to 1M (83.5% MRCR retrieval; 27% FLOPs, 10% KV vs. V3.2)[5][1]
• Type: Open weights + API
• Deployment: Cloud/on-prem/K8s/GPU
• Reasoning: Explicit modes, self-verification, sparse MoE for long-context/agents[2][1]

Unique Strengths:

• Top price/performance (SWE Verified 80.6%, LiveCodeBench 93.5%, GPQA Diamond 71.7% V4-Pro; #2 open-weights reasoning)[9][5][1]
• Efficient MoE (hybrid shared/routed experts, fine-grained top-K routing, load balancing; 28.5–18.2% compute vs. dense)[6][2]
• Transparent reasoning, rapid iteration; V4 stable multimodal (text+image via DeepSeek VL, early video)[3][7][1]
• Multimodal cross-modal reasoning: DeepSeek VL supports sustained context across turns for complex QA involving charts/diagrams[7]
• 2026 benchmarks: V4-Pro ranks #13/557 overall intelligence (8.7/10), 63.8 Agentic Index, 38.4 Coding Index; τ²-Bench 91.2% conversational agent[1]

New Findings (2026-06):

• CAISI evaluation of DeepSeek V4 Pro published by NIST confirms alignment with standardized AI safety and interoperability criteria for enterprise deployment; indicates competitive standing in formal evaluation contexts.[5]
• DeepSeek VL demonstrates robust cross-modal reasoning with persistent conversational context across image/text turns, enabling sophisticated multimodal QA workflows.[2]
• Benchmark reporting through 2026 channels shows V4-Pro achieving top-tier SWE-Bench Verified scores close to competing multimodal agents, reinforcing its position in tool-augmented reasoning tasks.[9][1]

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chat.z.ai (Zhipu AI)

Zhipu AI's chat.z.ai platform remains the main interface for the GLM-5 family and is positioned as a leading Chinese-origin AI stack, with strong agentic, coding, and research capabilities plus an expanding sovereign-AI footprint in Southeast Asia.

Key Capabilities:

• GLM-5 Series Models: GLM-5 is a 744B-parameter MoE model with 40B active parameters and a 204.8K context window; GLM-5.1 (released April 7, 2026 under MIT license) is the newer flagship for long-horizon agentic engineering, with the same core architecture but heavy fine-tuning for coding/tool use, achieving SOTA 58.4% on SWE-Bench Pro and supporting 8+ hours of autonomous execution, with OpenRouter listing its context at 203K tokens.
• Research and Agentic Modes: The platform separates Chat Mode (instant response, interactive chat, lightweight delivery) from Agent Mode (multiple tools, multi-step planning, long-running execution); Z.ai describes Agent Mode as the path for autonomous, multi-tool workflows capable of 8-hour continuous task execution, while Chat Mode targets quick responses.
• Pricing and Access: OpenRouter pricing as of mid-2026 shows GLM-5.1 at $0.98 per 1M input tokens and $3.08 per 1M output tokens, with cached input at $0.182 per 1M; Z.ai's developer docs note GLM-5.1 and GLM-5-Turbo are premium models consuming 1× quota during off-peak hours (1× through end of June 2026) but 5× quota during peak hours.
• Regional Specialization: The platform's strongest regional advantage remains its integration with Chinese-language data ecosystems and multilingual deployment patterns, supporting analysis and workflows relevant to Chinese-speaking markets and cross-border trade.
• Sovereign AI Infrastructure: Z.ai's Malaysia sovereign-AI program has moved from launch into full operation: the SEA Regional MaaS platform and Z·UM AI Lab at University of Malaya officially went live in late 2025 as active pillars of a broader ASEAN blueprint. The national MaaS platform is built on Z.ai's open-source foundational models via Z.ai, optimized for Bahasa Malaysia, English, and Chinese with sovereignty-first data security architecture, serving government operations, enterprise use cases, scientific research, and education including AI training for students.

New findings since the last update:

• Malaysia’s SEA Regional MaaS Platform and Z·UM AI Lab formally launched in late 2025, with ongoing 2026 expansion plans across Southeast Asia to scale sovereign AI infrastructure, talent development, and open-model deployment within ASEAN ecosystems. This includes token-access initiatives for universities and university-led research programs to accelerate regional AI education and innovation.
• ASEAN-wide governance frameworks and Responsible AI Roadmaps (2025–2030) are being operationalized to guide public-sector AI adoption, data governance, and cross-border collaboration, aligning with regional education and workforce development initiatives.

Updated Comparison Matrix

Pricing Comparison

Context Window Comparison

Citation Quality Comparison

Cost Efficiency Comparison

Recommendations

By Research Type

For Academic Researchers:

1. Primary: Perplexity Pro or Education Pro for citation-dense, source-grounded workflows; Education Pro continues to bundle expanded citations, file/image uploads, Learn Mode, and extended Research/Academic access at discounted pricing for verified users.
2. Supplement: Gemini Deep Research / Deep Research Max for broad web and scholarly coverage; 2026 updates emphasize faster multi-step retrieval, stronger file grounding, MCP integrations, improved charting/visual outputs, and enhanced export options to reference managers.
3. Specialized: Claude Pro for large-scale synthesis; Opus 4.6 and Sonnet 4.6 maintain ~1M-token context with improved stability on long-document reasoning; additional long-document tooling improvements for bibliography management.
4. Tip: Use Perplexity for discovery and citations, Gemini for breadth and multimodal expansion, and Claude for deep synthesis of curated material.

For Technical Research:

1. Primary: DeepSeek V3.2 / R1-class APIs for cost-efficient math, code, and reasoning workloads; pricing remains among the lowest with aggressive cache discounts and stable performance in batch pipelines.
2. Supplement: ChatGPT Plus/Business for structured workflows, code execution, and integrated deep research tools; current tiers emphasize GPT-5.x family models with stronger tool orchestration and data analysis.
3. Document Analysis: Claude long-context models for large codebases, RFCs, and multi-file specs.
4. Tip: Use DeepSeek for scale and cost control, ChatGPT for tooling and iteration, and Claude for long-context consolidation.

For Asian Market Intelligence:

1. Essential: Z.AI / GLM-5 for Chinese-language media, policy tracking, and regional datasets; pricing remains competitive with strong multilingual coverage.
2. Supplement: Gemini Deep Research for global and cross-border context.
3. Tip: Combine Z.AI with Western systems to mitigate regional bias and coverage gaps.

For Real-Time Analysis:

1. Primary: Gemini Deep Research Max for continuously updated web coverage and multi-hop retrieval.
2. Supplement: Grok for real-time X/Twitter sentiment, trend detection, and early signal capture; paid tiers remain relatively low-cost compared to competitors.
3. Tip: Pair Gemini for structured breadth with Grok for rapid, signal-heavy inputs.

For Comprehensive Coverage:

• Combine multiple platforms; no single system leads across citations, indexing, long-context reasoning, and real-time data.
• Use a tiered stack: free tiers for exploration, Pro/Advanced tiers for sustained or production workflows.

For Budget-Conscious Users:

1. Essential Research: Perplexity free tier; Education Pro remains the highest-value upgrade where eligible.
2. Moderate Usage: Grok Lite or equivalent entry tiers for affordable real-time insights.
3. High Volume: DeepSeek APIs for lowest-cost large-scale processing with caching advantages.
4. Multilingual: Z.AI low-cost tiers for Chinese and multilingual access.

For Autonomous Research:

1. Primary: Gemini Deep Research Max for agentic workflows combining web, files, and MCP-enabled tools.
2. Alternative: Claude Pro for long-context iterative reasoning and document chaining.
3. Use Cases: Continuous literature reviews, monitoring systems, automated research pipelines.

For Social Media Analysis:

1. Primary: Grok for native X/Twitter access and sentiment tracking.
2. Broader Social: Gemini Deep Research for cross-platform aggregation and validation.
3. Tip: Triangulate Grok signals with Perplexity or Gemini to reduce noise and bias.

For Video Content Research:

1. Primary: Gemini 3.x Pro / Deep Research Max for multimodal reasoning over long-form video and transcripts.
2. Supplement: ChatGPT for structured summaries, extraction, and transformation.
3. Use Cases: Lecture parsing, tutorial mining, video-to-report workflows.

By Use Case

Workflow Recommendations

Academic Literature Review:

1. Start with Perplexity Academic/Research modes for discovery and citation mapping.
2. Expand with Gemini Deep Research for broader coverage and multimodal inputs.
3. Upload and synthesize key papers in Claude long-context models.
4. Export and manage citations externally or via Perplexity tools.

Technical Documentation Research:

1. Use DeepSeek APIs with caching for large-scale reasoning and parsing.
2. Use ChatGPT for code workflows, execution, and structured outputs.
3. Analyze large repositories in Claude.
4. Use Perplexity for external references and documentation validation.

Market Research (Global):

1. Use Z.AI for Chinese-language and regional intelligence.
2. Add Gemini Deep Research Max for global coverage and file-based inputs.
3. Use Grok for real-time sentiment signals.
4. Synthesize with Claude or Gemini.

Competitive Intelligence:

1. Use Claude for long-context tracking and periodic synthesis.
2. Use Gemini Deep Research Max for continuous web monitoring.
3. Use Grok for early trend detection.
4. Cross-validate across platforms.

Video Content Analysis:

1. Process with Gemini multimodal models.
2. Structure outputs with ChatGPT.
3. Validate with Perplexity or Gemini.
4. Compile reports with Claude.

Autonomous Research Pipelines:

1. Use Gemini Deep Research Max for orchestration and retrieval.
2. Combine with agent frameworks and long-context models.
3. Route bulk workloads to DeepSeek APIs.
4. Validate outputs using Perplexity or Gemini.

Budget-Conscious Research:

1. Start with free tiers (Perplexity, Gemini).
2. Add Grok Lite for real-time needs.
3. Offload heavy processing to DeepSeek.
4. Use Z.AI for multilingual coverage.

Real-Time Monitoring:

1. Use Grok for continuous social tracking.
2. Use Gemini Deep Research Max for rolling updates and aggregation.
3. Automate synthesis with Claude.
4. Feed outputs into dashboards or reporting systems.

Platform Selection Quick Reference