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BenchLM
Google logo
Model A
Gemma 4 31B

Google

60.39/100

Supported · Public rank #66

90% interval 44.0–76.8

Gemma 4 31B vs Hy4 preview

Updated August 28, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Tencent logo
Model B
Hy4 preview

Tencent

79.16/100

Estimated · Public rank #7

90% interval 69.3–89.0

Decision reading

Hy4 preview has the higher public score estimate, 79.16 versus 60.39, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

3 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

    Hy4 preview

    Hy4 preview 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
3
Gemma 4 31B only
5
Hy4 preview only
25
Like-for-like categories
0 / 8

1 category uses 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
Hy4 preview
60.4
Weighted basis
3 vs 2 rows
Reading
Directional only

Agentic

Not comparable
Gemma 4 31B
Not measured
Hy4 preview
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Gemma 4 31B
41.6
Hy4 preview
65.7
Weighted basis
1 vs 1 rows
Reading
Not comparable

Reasoning

Not comparable
Gemma 4 31B
Not measured
Hy4 preview
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Math

Not comparable
Gemma 4 31B
Not measured
Hy4 preview
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Gemma 4 31B
Not measured
Hy4 preview
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Gemma 4 31B
76.9
Hy4 preview
66.2
Weighted basis
1 vs 1 rows
Reading
Not comparable

Instruction following

Not comparable
Gemma 4 31B
Not measured
Hy4 preview
Not measured
Weighted basis
0 vs 0 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
Hy4 preview
Self-hosted; infrastructure cost varies
Fits in one request

Gemma 4 31B has no comparable published API token rate. Hy4 preview 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
Hy4 preview
Self-hosted; infrastructure cost varies
Fits in one request

Gemma 4 31B has no comparable published API token rate. Hy4 preview 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
Hy4 preview
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Gemma 4 31B has no comparable published API token rate. Hy4 preview 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

Hy4 preview

No comparable hosted API rate

Tencent Hy4 preview model card

Provider availability

Gemma 4 31B

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

Google Gemma Gemini API guide

Hy4 preview

Not sourced

Reasoning profile

Gemma 4 31B

Reasoning

Hy4 preview

Reasoning

Weight access

Gemma 4 31B

Open Weight

Hy4 preview

Open Weight

License

Gemma 4 31B

Open Weight

Hy4 preview

Open Weight

Release date

Gemma 4 31B

2026-04-02

Hy4 preview

2026-08-28

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
Hy4 preview has the higher public score estimate, 79.16 versus 60.39, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Hy4 preview 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—
Hy4 preview
API / mo$0
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 evidence33 rows

Agentic

  • Gert Labs

    Gemma 4 31B35.26%
    Source
    Hy4 preview—

    Not directly comparable

  • Terminal-Bench 2.1

    Gemma 4 31B—
    Hy4 preview85.4%
    Source

    Not directly comparable

  • CyberGym

    Gemma 4 31B—
    Hy4 preview78.4%
    Source

    Not directly comparable

  • WideResearch

    Gemma 4 31B—
    Hy4 preview83.9%
    Source

    Not directly comparable

  • DRACO

    Gemma 4 31B—
    Hy4 preview77.2%
    Source

    Not directly comparable

  • MCP Atlas

    Gemma 4 31B—
    Hy4 preview83.7%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Gemma 4 31B—
    Hy4 preview74.1%
    Source

    Not directly comparable

  • APEX-Agents

    Gemma 4 31B—
    Hy4 preview37.1%
    Source

    Not directly comparable

  • skillsBench

    Gemma 4 31B—
    Hy4 preview62.9%
    Source

    Not directly comparable

  • JobBench

    Gemma 4 31B—
    Hy4 preview61.7%
    Source

    Not directly comparable

  • Agents' Last Exam

    Gemma 4 31B—
    Hy4 preview22.8%
    Source

    Not directly comparable

  • AutomationBench

    Gemma 4 31B—
    Hy4 preview32.1%
    Source

    Not directly comparable

  • BankerToolBench

    Gemma 4 31B—
    Hy4 preview78.6%
    Source

    Not directly comparable

  • HLE w/ tools

    Gemma 4 31B—
    Hy4 preview55.4%
    Source

    Not directly comparable

Coding

  • SWE-Rebench

    Gemma 4 31B41.6%
    Source
    Hy4 preview—

    Not directly comparable

  • React Native Evals

    Gemma 4 31B75.2%
    Source
    Hy4 preview—

    Not directly comparable

  • Terminal-Bench 2.1

    Gemma 4 31B—
    Hy4 preview85.4%
    Source

    Not directly comparable

  • SWE-bench Pro

    Gemma 4 31B—
    Hy4 preview65.7%
    Source

    Not directly comparable

  • SWE Multilingual

    Gemma 4 31B—
    Hy4 preview82.9%
    Source

    Not directly comparable

  • deepSwe

    Gemma 4 31B—
    Hy4 preview64.3%
    Source

    Not directly comparable

  • NL2Repo

    Gemma 4 31B—
    Hy4 preview58.9%
    Source

    Not directly comparable

  • ProgramBench

    Gemma 4 31B—
    Hy4 preview17.5%
    Source

    Not directly comparable

  • PostTrain Bench

    Gemma 4 31B—
    Hy4 preview35.6%
    Source

    Not directly comparable

  • sweMarathon

    Gemma 4 31B—
    Hy4 preview31.9%
    Source

    Not directly comparable

Reasoning

  • CritPt

    Gemma 4 31B—
    Hy4 preview16.9%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Gemma 4 31B84.3%
    Source
    Hy4 preview92.3%
    Source

    Hy4 preview leads this result

  • MMLU-Pro

    Gemma 4 31B85.2%
    Source
    Hy4 preview—

    Not directly comparable

  • HLE

    Gemma 4 31B26.5%
    Source
    Hy4 preview55.4%
    Source

    Hy4 preview leads this result

  • HLE w/o tools

    Gemma 4 31B19.5%
    Source
    Hy4 preview43.4%
    Source

    Hy4 preview leads this result

  • GPQA-D

    Gemma 4 31B—
    Hy4 preview92.3%
    Source

    Not directly comparable

Math

  • Apex

    Gemma 4 31B—
    Hy4 preview74.2%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Gemma 4 31B76.9%
    Source
    Hy4 preview—

    Not directly comparable

  • OfficeQA Pro

    Gemma 4 31B—
    Hy4 preview66.2%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Gemma 4 31B or Hy4 preview?

Hy4 preview has the higher public score estimate, 79.16 versus 60.39, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Gemma 4 31B or Hy4 preview?

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 Hy4 preview?

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 Hy4 preview?

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 Hy4 preview?

Hy4 preview has the larger documented context window: 1M, compared with 256K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 28, 2026

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