Model A

Google

60.39/100

Supported · Public rank #66

90% interval 44.0–76.8

Gemma 4 31B vs MiniMax M3

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

Model B

MiniMax M3

MiniMax

68.73/100

Supported · Public rank #21

90% interval 63.5–74.0

Decision reading

MiniMax M3 has the higher public score estimate, 68.73 versus 60.39, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

1 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
MiniMax M3
MiniMax M3 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.

7 Gemma 4 31B only

1 Shared

21 MiniMax M3 only

Shared results: 1
Gemma 4 31B only: 7
MiniMax M3 only: 21
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.

Multimodal

Directional only

Gemma 4 31B: 76.9
MiniMax M3: 64.9
Weighted basis: 1 vs 2 rows
Reading: Directional only

Agentic

Not comparable

Gemma 4 31B: Not measured
MiniMax M3: 72.3
Weighted basis: 0 vs 3 rows
Reading: Not comparable

Coding

Not comparable

Gemma 4 31B: 41.6
MiniMax M3: 72.2
Weighted basis: 1 vs 2 rows
Reading: Not comparable

Reasoning

Not comparable

Gemma 4 31B: Not measured
MiniMax M3: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Knowledge

Not comparable

Gemma 4 31B: 52.9
MiniMax M3: Not measured
Weighted basis: 3 vs 0 rows
Reading: Not comparable

Math

Not comparable

Gemma 4 31B: Not measured
MiniMax M3: 85.7
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Multilingual

Not comparable

Gemma 4 31B: Not measured
MiniMax M3: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Instruction following

Not comparable

Gemma 4 31B: Not measured
MiniMax M3: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Category averages with the server-provided evidence basis for Gemma 4 31B and MiniMax M3
Category	Gemma 4 31B	MiniMax M3	Weighted basis	Reading
Multimodal	76.9	64.9	Directional only1 vs 2 rows	Directional only
Agentic	Not measured	72.3	Not comparable0 vs 3 rows	Not comparable
Coding	41.6	72.2	Not comparable1 vs 2 rows	Not comparable
Reasoning	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Knowledge	52.9	Not measured	Not comparable3 vs 0 rows	Not comparable
Math	Not measured	85.7	Not comparable0 vs 1 rows	Not comparable
Multilingual	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Instruction following	Not measured	Not measured	Not comparable0 vs 0 rows	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.

MMMU-Pro
Multimodal
Gemma 4 31B: 76.9%MiniMax M3: 78.1%Normalized gap 1.2Gemma 4 31B source MiniMax M3 source

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
MiniMax M3: $0.0009; 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
MiniMax M3: $0.0186; 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
MiniMax M3: $0.03; Fits in one request

Reasoning

MiniMax M3

Non-Reasoning

Weight access

Gemma 4 31B

Open Weight

MiniMax M3

Open Weight

License

Gemma 4 31B

Open Weight

MiniMax M3

Open Weight

Release date

Gemma 4 31B

2026-04-02

MiniMax M3

2026-06-01

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: MiniMax M3 has the higher public score estimate, 68.73 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: MiniMax M3 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—

MiniMax M3

API / mo$1,125

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 evidence29 rows

Agentic

Gert Labs
Gemma 4 31B35.26%
Source
MiniMax M3—
Not directly comparable
Terminal-Bench 2.0
Gemma 4 31B—
MiniMax M366%
Source
Not directly comparable
BrowseComp
Gemma 4 31B—
MiniMax M383.5%
Source
Not directly comparable
OSWorld-Verified
Gemma 4 31B—
MiniMax M370.1%
Source
Not directly comparable
MCP Atlas
Gemma 4 31B—
MiniMax M374.2%
Source
Not directly comparable
Claw-Eval
Gemma 4 31B—
MiniMax M374.5%
Source
Not directly comparable
BankerToolBench
Gemma 4 31B—
MiniMax M376.1%
Source
Not directly comparable
ResearchClawBench
Gemma 4 31B—
MiniMax M319.8%
Source
Not directly comparable
OSWorld 2.0
Gemma 4 31B—
MiniMax M34.6%
Source
Not directly comparable

Coding

SWE-Rebench
Gemma 4 31B41.6%
Source
MiniMax M3—
Not directly comparable
React Native Evals
Gemma 4 31B75.2%
Source
MiniMax M3—
Not directly comparable
SWE-bench Verified
Gemma 4 31B—
MiniMax M380.5%
Source
Not directly comparable
SWE-bench Pro
Gemma 4 31B—
MiniMax M359%
Source
Not directly comparable
Terminal-Bench 2.0
Gemma 4 31B—
MiniMax M366.0%
Source
Not directly comparable
NL2Repo
Gemma 4 31B—
MiniMax M342.1%
Source
Not directly comparable
VIBE V2
Gemma 4 31B—
MiniMax M350.1%
Source
Not directly comparable
SVG-Bench
Gemma 4 31B—
MiniMax M363.7%
Source
Not directly comparable
KernelBench Hard
Gemma 4 31B—
MiniMax M328.8%
Source
Not directly comparable
OpenHarmony Bench
Gemma 4 31B—
MiniMax M348.4%
Source
Not directly comparable

Knowledge

GPQA
Gemma 4 31B84.3%
Source
MiniMax M3—
Not directly comparable
MMLU-Pro
Gemma 4 31B85.2%
Source
MiniMax M3—
Not directly comparable
HLE
Gemma 4 31B26.5%
Source
MiniMax M3—
Not directly comparable
HLE w/o tools
Gemma 4 31B19.5%
Source
MiniMax M3—
Not directly comparable

Math

USAMO 2026
Gemma 4 31B—
MiniMax M385.7%
Source
Not directly comparable

Multimodal

MMMU-Pro
Gemma 4 31B76.9%
Source
MiniMax M378.1%
Source
MiniMax M3 leads this result
OfficeQA Pro
Gemma 4 31B—
MiniMax M345.1%
Source
Not directly comparable
OmniDocBench 1.5
Gemma 4 31B—
MiniMax M391.6%
Source
Not directly comparable
VideoMMMU
Gemma 4 31B—
MiniMax M384.6%
Source
Not directly comparable
Video-MME (with subtitle)
Gemma 4 31B—
MiniMax M385.4%
Source
Not directly comparable

Frequently asked questions

Which is better, Gemma 4 31B or MiniMax M3?

MiniMax M3 has the higher public score estimate, 68.73 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 MiniMax M3?

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 MiniMax M3?

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 MiniMax M3?

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 MiniMax M3?

MiniMax M3 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 30, 2026

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Gemma 4 31B vs MiniMax M3

Which one for your work

Long documents

Coding work

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

What is actually comparable

Category results, on a stated basis

Multimodal

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Instruction following

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Self-host vs API cost

Benchmark evidence

Agentic

Coding

Knowledge

Math

Multimodal

Frequently asked questions

Which is better, Gemma 4 31B or MiniMax M3?

Which is better for coding, Gemma 4 31B or MiniMax M3?

Which is better for agentic tasks, Gemma 4 31B or MiniMax M3?

Which costs less, Gemma 4 31B or MiniMax M3?

Which has the larger context window, Gemma 4 31B or MiniMax M3?

Related comparisons

Watch Gemma 4 31B vs MiniMax M3