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BenchLM
Model A
Gemini 3.7 Flash

Google

—

Evidence status unavailable

90% interval unavailable

Gemini 3.7 Flash vs MiniMax M3

Updated August 13, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
MiniMax M3

MiniMax

68.5/100

Supported · Public rank #19

90% interval 63.5–73.5

Decision reading

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

  • Chat turn cost

    1K fresh input + 500 output tokens

    MiniMax M3

    MiniMax M3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

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

    MiniMax M3

    MiniMax M3 has the lower estimated token cost for this stated workload. Gemini 3.7 Flash has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

Show secondary and unsupported calls

  • Repository review cost

    50K fresh input + 3K output tokens

    MiniMax M3

    MiniMax M3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • 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

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

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
1
Gemini 3.7 Flash only
14
MiniMax M3 only
21
Like-for-like categories
0 / 8

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.

Agentic

Not comparable
Gemini 3.7 Flash
Not measured
MiniMax M3
72.3
Weighted basis
0 vs 3 rows
Reading
Not comparable

Coding

Not comparable
Gemini 3.7 Flash
Not measured
MiniMax M3
72.2
Weighted basis
0 vs 2 rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 3.7 Flash
Not measured
MiniMax M3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Gemini 3.7 Flash
Not measured
MiniMax M3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Math

Not comparable
Gemini 3.7 Flash
Not measured
MiniMax M3
85.7
Weighted basis
0 vs 1 rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.7 Flash
Not measured
MiniMax M3
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.7 Flash
88.7
MiniMax M3
64.9
Weighted basis
1 vs 2 rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.7 Flash
Not measured
MiniMax M3
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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

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

Gemini 3.7 Flash
$0.00262
Fits in one request
MiniMax M3
$0.0009
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Gemini 3.7 Flash
$0.04875
Fits in one request
MiniMax M3
$0.0186
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Gemini 3.7 Flash
$0.2025
Fits in one request
Cached input priced at the published list-input rate
MiniMax M3
$0.03
Fits in one request

MiniMax M3 has the lower modeled cost

Gemini 3.7 Flash has no published cached-input rate, so cached tokens use its listed input 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.

Gemini 3.7 Flash

Not published

Google: Introducing Gemini 3.7 Flash

MiniMax M3

$0.06 per 1M cached input tokens

Provider availability

Gemini 3.7 Flash

Generally Available · Gemini API, Google AI Studio, Google Antigravity, Gemini Enterprise Agent Platform, Gemini Enterprise, Gemini app via Spark

Google Gemini 3.7 Flash launch

MiniMax M3

Not sourced

Reasoning profile

Gemini 3.7 Flash

Reasoning

MiniMax M3

Non-Reasoning

Weight access

Gemini 3.7 Flash

Proprietary

MiniMax M3

Open Weight

License

Gemini 3.7 Flash

Proprietary

MiniMax M3

Open Weight

Release date

Gemini 3.7 Flash

2026-08-13

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
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
Repository review: $0.04875 vs $0.0186. Cache-heavy agent loop: $0.2025 vs $0.03.
Context tradeoff
Both models list 1M.

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

Benchmark evidence

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

Browse raw public benchmark evidence36 rows

Agentic

  • Terminal-Bench 2.1

    Gemini 3.7 Flash85.8%
    Source
    MiniMax M3—

    Not directly comparable

  • Terminal-Bench 3.0

    Gemini 3.7 Flash14.9%
    Source
    MiniMax M3—

    Not directly comparable

  • AutomationBench

    Gemini 3.7 Flash30.4%
    Source
    MiniMax M3—

    Not directly comparable

  • OSWorld 2.0

    Gemini 3.7 Flash47.9%
    Source
    MiniMax M34.6%
    Source

    Gemini 3.7 Flash leads this result

  • Agents' Last Exam

    Gemini 3.7 Flash26.3%
    Source
    MiniMax M3—

    Not directly comparable

  • Terminal-Bench 2.0

    Gemini 3.7 Flash—
    MiniMax M366%
    Source

    Not directly comparable

  • BrowseComp

    Gemini 3.7 Flash—
    MiniMax M383.5%
    Source

    Not directly comparable

  • OSWorld-Verified

    Gemini 3.7 Flash—
    MiniMax M370.1%
    Source

    Not directly comparable

  • MCP Atlas

    Gemini 3.7 Flash—
    MiniMax M374.2%
    Source

    Not directly comparable

  • Claw-Eval

    Gemini 3.7 Flash—
    MiniMax M374.5%
    Source

    Not directly comparable

  • BankerToolBench

    Gemini 3.7 Flash—
    MiniMax M376.1%
    Source

    Not directly comparable

  • ResearchClawBench

    Gemini 3.7 Flash—
    MiniMax M319.8%
    Source

    Not directly comparable

Coding

  • FrontierCode 1.1 Main

    Gemini 3.7 Flash43.6%
    Source
    MiniMax M3—

    Not directly comparable

  • deepSwe

    Gemini 3.7 Flash65.3%
    Source
    MiniMax M3—

    Not directly comparable

  • Terminal-Bench 2.1

    Gemini 3.7 Flash85.8%
    Source
    MiniMax M3—

    Not directly comparable

  • SWE-bench Verified

    Gemini 3.7 Flash—
    MiniMax M380.5%
    Source

    Not directly comparable

  • SWE-bench Pro

    Gemini 3.7 Flash—
    MiniMax M359%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Gemini 3.7 Flash—
    MiniMax M366.0%
    Source

    Not directly comparable

  • NL2Repo

    Gemini 3.7 Flash—
    MiniMax M342.1%
    Source

    Not directly comparable

  • VIBE V2

    Gemini 3.7 Flash—
    MiniMax M350.1%
    Source

    Not directly comparable

  • SVG-Bench

    Gemini 3.7 Flash—
    MiniMax M363.7%
    Source

    Not directly comparable

  • KernelBench Hard

    Gemini 3.7 Flash—
    MiniMax M328.8%
    Source

    Not directly comparable

  • EEBench

    Gemini 3.7 Flash—
    MiniMax M39.2%
    Source

    Not directly comparable

Reasoning

  • GDM-MRCR v2 128K average

    Gemini 3.7 Flash97%
    Source
    MiniMax M3—

    Not directly comparable

Knowledge

  • BioMysteryBench (human-solvable)

    Gemini 3.7 Flash87.1%
    Source
    MiniMax M3—

    Not directly comparable

  • BioMysteryBench (human-difficult)

    Gemini 3.7 Flash43.5%
    Source
    MiniMax M3—

    Not directly comparable

Math

  • USAMO 2026

    Gemini 3.7 Flash—
    MiniMax M385.7%
    Source

    Not directly comparable

Multimodal

  • GDP.pdf (no tools)

    Gemini 3.7 Flash34.0%
    Source
    MiniMax M3—

    Not directly comparable

  • CharXiv w/o tools

    Gemini 3.7 Flash84.5%
    Source
    MiniMax M3—

    Not directly comparable

  • CharXiv

    Gemini 3.7 Flash88.7%
    Source
    MiniMax M3—

    Not directly comparable

  • LVBench

    Gemini 3.7 Flash85.4%
    Source
    MiniMax M3—

    Not directly comparable

  • OfficeQA Pro

    Gemini 3.7 Flash—
    MiniMax M345.1%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Gemini 3.7 Flash—
    MiniMax M391.6%
    Source

    Not directly comparable

  • MMMU-Pro

    Gemini 3.7 Flash—
    MiniMax M378.1%
    Source

    Not directly comparable

  • VideoMMMU

    Gemini 3.7 Flash—
    MiniMax M384.6%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Gemini 3.7 Flash—
    MiniMax M385.4%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3.7 Flash or MiniMax M3?

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, Gemini 3.7 Flash 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, Gemini 3.7 Flash 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, Gemini 3.7 Flash or MiniMax M3?

For the stated presets, chat costs $0.00263 on Gemini 3.7 Flash and $0.0009 on MiniMax M3; repository review costs $0.04875 and $0.0186; the cache-heavy agent loop costs $0.2025 and $0.03. Gemini 3.7 Flash has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Gemini 3.7 Flash or MiniMax M3?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 13, 2026

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