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Model Comparison

GPT-5.1-Codex-Max vs Inkling SmallWhich Is Better in 2026?

GPT-5.1-Codex-Max vs Inkling Small: which should you choose in 2026?

GPT-5.1-Codex-Max (by OpenAI) and Inkling Small (by Thinkingmachines) are compared below. Here is how they stack up on benchmarks, price, and capabilities, and which one to pick in 2026.

There are not enough shared, protocol-compatible benchmark results to declare a performance leader.

Inkling Small is about 5.4× cheaper on a blended 3:1 input/output basis ($0.64 vs $3.44 per 1M tokens).

Inkling Small has the larger context window (524,288 tokens vs 400,000 tokens).

Choose GPT-5.1-Codex-Max if…

  • your own prompt tests favor its output; shared comparable evidence does not identify a unique advantage

Choose Inkling Small if…

  • lower blended API cost matters for your workload
  • you work with longer documents, transcripts, or codebases

The benchmark count includes only results measured with a matching benchmark version and protocol. Arena scores are shown separately. Missing, preliminary, and incompatible data is not treated as a controlled win. Published point-score comparisons are labeled separately when protocol details are incomplete. For text-output models, the verdict also compares token pricing and context windows.

vs

Performance benchmarks

Every value links to its source. A dash means that no reviewed result is available for that exact model and protocol.

GPT-5.1-Codex-Max and Inkling Small benchmark results
BenchmarkGPT-5.1-Codex-MaxInkling Small
AutomationBench-AA

A 657-task benchmark of multi-step work across simulated SaaS applications in six business domains. The Artificial Analysis protocol reports a guardrail-aware score and is distinct from both the public Zapier split and the unrelated dynamic AutoBench framework.

Guardrail-aware score

BrowseComp

A benchmark of difficult, verifiable information-seeking questions designed to measure an agent's ability to locate hard-to-find facts through web browsing.

Accuracy

OSWorld-Verified

A verified computer-use benchmark in which multimodal agents operate desktop applications and are graded from the resulting environment state.

Mean task reward

SWE-Bench Verified

A human-validated subset of real GitHub issues used to measure whether a coding agent can produce repository patches that resolve the associated tests.

Resolved

Terminal-Bench 2.1

Version 2.1 of the benchmark for completing realistic tasks in terminal environments. Harness, resource limits, and attempt count are part of the protocol.

Mean task success

GPQA Diamond

The highest-quality subset of Graduate-Level Google-Proof Q&A, designed to test expert-level scientific reasoning in biology, physics, and chemistry.

Accuracy

Humanity's Last Exam

A 2,500-question expert-level benchmark spanning dozens of academic fields. Tool-assisted and no-tools results are separate protocols and must not be merged.

Accuracy

Benchmark sources

    Reviewed evidence last updated 2026-08-09.

    Pricing, capabilities, and model facts

    GPT-5.1-Codex-Max and Inkling Small model facts
    FeatureGPT-5.1-Codex-MaxInkling Small
    Context & model facts
    DeveloperOpenAIThinkingmachines
    API providerOpenAIThinking Machines
    Input context400,000 tokens524,288 tokens
    Maximum output128,000 tokens262,144 tokens
    Released
    Added to WritingmateDec 4, 2025Jul 30, 2026
    License
    Knowledge cutoff
    Capabilities
    InputsText, ImageText, Image, Audio
    OutputsTextText
    Tool useYesYes
    ReasoningYesYes
    VisionYesYes
    Image GenerationNoNo
    Video GenerationNoNo
    API pricing
    Input (per 1M tokens)$1.25$0.45
    Output (per 1M tokens)$10.00$1.20
    Blended 3:1 input/output$3.44$0.64
    API performance
    p95 latencyNot measuredNot measured
    Output throughputNot measuredNot measured
    Writingmate shows API performance only when both models have enough observations from the same measurement window, prompt profile, and provider. Third-party latency values are not copied into this table.

    Data sources

    • Writingmate model catalog (pricing, limits, and availability)

    Catalog data last updated Jul 30, 2026.

    Why Pay for Multiple Subscriptions?

    Comparing GPT-5.1-Codex-Max from OpenAI with Inkling Small from Thinkingmachines? Instead of managing separate API keys and subscriptions, get both with Writingmate.

    Subscription-plan access for GPT-5.1-Codex-Max and Inkling Small
    PlanPriceGPT-5.1-Codex-MaxInkling SmallAI ImagesAI Video
    Writingmate Pro
    Most popular
    $20/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1
    Writingmate Ultimate
    Power users
    $60/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreSora 2, VEO 3.1

    GPT-5.1-Codex-Max vs Inkling Small FAQ

    Which is better, GPT-5.1-Codex-Max or Inkling Small?

    There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Inkling Small is about 5.4× cheaper on a blended 3:1 input/output basis ($0.64 vs $3.44 per 1M tokens). Inkling Small has the larger context window (524,288 tokens vs 400,000 tokens).

    Which model is cheaper to use through an API?

    Inkling Small is about 5.4× cheaper on a blended 3:1 input/output basis ($0.64 vs $3.44 per 1M tokens).

    Which model supports more context?

    Inkling Small has the larger context window (524,288 tokens vs 400,000 tokens).

    Can I switch between GPT-5.1-Codex-Max and Inkling Small?

    Yes. Use the model selector on this page to open any current Writingmate model comparison. You can also run the same prompt with both models in Writingmate.