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Model comparison

Gemma 4 31B vs Inkling-Small

Updated July 30, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Gemma 4 31B

Google

60.2/100

Supported · Public rank #47

90% interval 44.6–75.8

Inkling-Small

Thinking Machines Lab

Evidence status unavailable

90% interval unavailable

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

4 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Long documents

    Prompts that approach the documented context limit

    Inkling-Small

    Inkling-Small has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
4
Gemma 4 31B only
4
Inkling-Small only
16
Like-for-like categories
0 / 8

2 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Knowledge

Directional only
Gemma 4 31B
52.9
Inkling-Small
53.4
Weighted basis
3 vs 2 rows
Reading
Directional only

Multimodal

Directional only
Gemma 4 31B
76.9
Inkling-Small
76.6
Weighted basis
1 vs 2 rows
Reading
Directional only

Agentic

Not comparable
Gemma 4 31B
Not measured
Inkling-Small
70.1
Weighted basis
0 vs 2 rows
Reading
Not comparable

Coding

Not comparable
Gemma 4 31B
41.6
Inkling-Small
62.4
Weighted basis
1 vs 3 rows
Reading
Not comparable

Reasoning

Not comparable
Gemma 4 31B
Not measured
Inkling-Small
40.1
Weighted basis
0 vs 1 rows
Reading
Not comparable

Math

Not comparable
Gemma 4 31B
Not measured
Inkling-Small
92.9
Weighted basis
0 vs 2 rows
Reading
Not comparable

Multilingual

Not comparable
Gemma 4 31B
Not measured
Inkling-Small
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Gemma 4 31B
Not measured
Inkling-Small
82.2
Weighted basis
0 vs 1 rows
Reading
Not comparable

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Gemma 4 31B
Self-hosted; infrastructure cost varies
Fits in one request
Inkling-Small
$0.0013
Fits in one request

Gemma 4 31B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Gemma 4 31B
Self-hosted; infrastructure cost varies
Fits in one request
Inkling-Small
$0.03332
Fits in one request

Gemma 4 31B has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Gemma 4 31B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable
Inkling-Small
$0.0492
Fits in one request

Gemma 4 31B has no comparable published API token rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Gemma 4 31B

No comparable hosted API rate

Inkling-Small

$0.116 per 1M cached input tokens

Provider availability

Gemma 4 31B

Generally Available · Gemini API, Google AI Studio, open weights

Google Gemma Gemini API guide

Inkling-Small

Not sourced

Reasoning profile

Gemma 4 31B

Reasoning

Inkling-Small

Hybrid

Weight access

Gemma 4 31B

Open Weight

Inkling-Small

Open Weight

License

Gemma 4 31B

Open Weight

Inkling-Small

Open Weight

Release date

Gemma 4 31B

2026-04-02

Inkling-Small

2026-07-30

If you already use one of these models
Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Inkling-Small has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Gemma 4 31B
API / mo$0
Self-host / mo$429
Break-even
Inkling-Small
API / mo$1,515
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Model the full break-even

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence24 rows

Agentic

  • Gert Labs

    Gemma 4 31B35.26%
    Source
    Inkling-Small

    Not directly comparable

  • Terminal-Bench 2.0

    Gemma 4 31B
    Inkling-Small64.7%
    Source

    Not directly comparable

  • BrowseComp

    Gemma 4 31B
    Inkling-Small77.4%
    Source

    Not directly comparable

  • MCP Atlas

    Gemma 4 31B
    Inkling-Small79.6%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Gemma 4 31B
    Inkling-Small54.4%
    Source

    Not directly comparable

Coding

  • SWE-Rebench

    Gemma 4 31B41.6%
    Source
    Inkling-Small

    Not directly comparable

  • React Native Evals

    Gemma 4 31B75.2%
    Source
    Inkling-Small

    Not directly comparable

  • SWE-bench Verified

    Gemma 4 31B
    Inkling-Small80.2%
    Source

    Not directly comparable

  • SWE-bench Pro

    Gemma 4 31B
    Inkling-Small55.9%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Gemma 4 31B
    Inkling-Small64.7%
    Source

    Not directly comparable

  • SciCode

    Gemma 4 31B
    Inkling-Small48.7%
    Source

    Not directly comparable

Reasoning

  • ARC-AGI-2

    Gemma 4 31B
    Inkling-Small40.1%
    Source

    Not directly comparable

  • CritPt

    Gemma 4 31B
    Inkling-Small8.3%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Gemma 4 31B84.3%
    Source
    Inkling-Small89.5%
    Source

    Inkling-Small leads this result

  • MMLU-Pro

    Gemma 4 31B85.2%
    Source
    Inkling-Small

    Not directly comparable

  • HLE

    Gemma 4 31B26.5%
    Source
    Inkling-Small47.8%
    Source

    Inkling-Small leads this result

  • HLE w/o tools

    Gemma 4 31B19.5%
    Source
    Inkling-Small31.6%
    Source

    Inkling-Small leads this result

  • GPQA-D

    Gemma 4 31B
    Inkling-Small89.5%
    Source

    Not directly comparable

Math

  • AIME26

    Gemma 4 31B
    Inkling-Small95.5%
    Source

    Not directly comparable

  • HMMT Feb 2026

    Gemma 4 31B
    Inkling-Small90.2%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Gemma 4 31B76.9%
    Source
    Inkling-Small74%
    Source

    Gemma 4 31B leads this result

  • CharXiv

    Gemma 4 31B
    Inkling-Small81.3%
    Source

    Not directly comparable

  • CharXiv w/o tools

    Gemma 4 31B
    Inkling-Small77.4%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Gemma 4 31B
    Inkling-Small82.2%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Gemma 4 31B or Inkling-Small?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Gemma 4 31B or Inkling-Small?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Gemma 4 31B or Inkling-Small?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Gemma 4 31B or Inkling-Small?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Gemma 4 31B or Inkling-Small?

Inkling-Small has the larger documented context window: 1M, compared with 256K.

Related comparisons

Last updated July 30, 2026

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