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Build an AI-powered workflow · Agents and tool-using workflows

Best AI model for agents — November 2026

On BenchLM's public evidence, Claude Opus 5.5 has the highest agentic score estimate among the models that meet this page's constraints (89.3). A harness, tools, retries, and permissions are part of the measured system.

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The shortlist for agents

Constraints on this page: a builder choosing by accuracy, hosted processing allowed, any price, ordinary input size. Change any of them under Refine. A small score gap does not establish a reliably better model.

Compare Claude Opus 5.5 vs Claude Fable 5.1Full agentic leaderboard

  1. 01Claude Opus 5.5Best fit

    Anthropic · Proprietary

    89.3

    Agentic score estimate

    • Highest agentic estimate among candidates passing the measured filters
    • $8.00 for the stated workload
    • 1M context
    • Anthropic lists the model ID on each documented platform. Access details · checked September 22, 2026.
    • Provider API offer: Claude API. Check which models qualify and whether payment details are required. Limits and source.

    Estimate sources: LiveBench Agentic Coding

    Model page and evidence

  2. 02Claude Fable 5.1

    Anthropic · Proprietary

    80.1

    Agentic score estimate

    • Estimate 80.1 on the same agentic evidence
    • $20.00 for the stated workload
    • 1M context
    • Anthropic says Fable 5.1 is available on all platforms. Enterprise Frontier Safeguards will roll out in phases; eligible customers can use zero data retention until EFS is ready. Access details · checked September 1, 2026.
    • Provider API offer: Claude API. Check which models qualify and whether payment details are required. Limits and source.

    Estimate sources: Artificial Analysis, LiveBench Agentic Coding, Vals AI agentic-task composite

    Model page and evidenceCompare with Claude Opus 5.5

  3. 03Gemini 4 Argon

    Google · Proprietary

    77.7

    Agentic score estimate

    • Estimate 77.7 on the same agentic evidence
    • $4.00 for the stated workload
    • 1M context
    • Google lists gemini-4-argon as a stable model. Access details · checked October 13, 2026.
    • Provider API offer: Gemini API (Google AI Studio). Check which models qualify and whether payment details are required. Limits and source.

    Estimate sources: Scale Labs agentic composite

    Model page and evidenceCompare with Claude Opus 5.5

  4. 04GPT-6.1 Terra

    OpenAI · Proprietary

    76.0

    Agentic score estimate

    • Estimate 76.0 on the same agentic evidence
    • $2.00 for the stated workload
    • 1.05M context
    • OpenAI launched gpt-6.1-terra in the API and in ChatGPT Work and Codex for Plus, Pro, Enterprise, and Edu users. Use Responses for tool calling; Chat Completions supports the model without tool calling. Access details · checked October 26, 2026.
    • Provider API offer: OpenAI API, Free usage tier. Check which models qualify and whether payment details are required. Limits and source.

    Model page and evidenceCompare with Claude Opus 5.5

  5. 05GPT-6.1 Sol

    OpenAI · Proprietary

    75.8

    Agentic score estimate

    • Estimate 75.8 on the same agentic evidence
    • $4.00 for the stated workload
    • 1.05M context
    • OpenAI lists GPT-6.1 Sol as an API model. Use Responses for tool calling; Chat Completions supports the model without tool calling. Access details · checked September 29, 2026.
    • Provider API offer: OpenAI API, Free usage tier. Check which models qualify and whether payment details are required. Limits and source.

    Estimate sources: LiveBench Agentic Coding

    Model page and evidenceCompare with Claude Opus 5.5

Refine for your situation

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Describe the task and constraints. This selector recommends models; it cannot carry out the task or access your files and accounts.

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What this shortlist rests on

The agentic surface. Each model’s estimate names its own sources above; these are the public weighted benchmarks for the category.

What to verify before choosing

  • A harness, tools, retries, and permissions are part of the measured system.
  • Composite scores are estimates. A small score gap does not establish a reliably better model.

Try three representative examples of your own work. Compare errors, time, cost, and the tools available in your actual setup.

Questions

Which AI model is best for agents?

On BenchLM's public evidence, Claude Opus 5.5 by Anthropic has the highest agentic score estimate among models that meet the page's default constraints (89.3). Ordered by task score under the stated constraints. A harness, tools, retries, and permissions are part of the measured system.

What are the alternatives to Claude Opus 5.5 for agents?

Claude Fable 5.1 (80.1), Gemini 4 Argon (77.7), GPT-6.1 Terra (76.0), GPT-6.1 Sol (75.8) follow on the same evidence. A small gap does not establish a reliably better model; compare them on three representative examples of your own work.

How does BenchLM pick the best ai model for agents?

The page runs the LLM Selector with fixed answers: a builder choosing by accuracy, hosted processing allowed, any price, ordinary input size. The selector uses the agentic evidence surface, filters by the stated constraints, and orders by that evidence. It never adds a hidden fit score or a bonus for open weights or reasoning style.

Can I change the constraints?

Yes. Every link under "Refine" opens the selector with one answer changed, and the address carries the answers so a result can be shared or reopened against the current dataset.

Method: bench-align-v5.8-2026-09-30. Read the methodology and benchmark confidence pages for how scores and verification statuses are produced.

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