Skip to main content
BenchLM

Gemini 3.7 Flash vs MiniMax M2.7

Updated September 27, 2026. Rank says Gemini 3.7 Flash is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Share or export
Share on XLinkedInSocial cardCSVJSON

Decision reading

Gemini 3.7 Flash has the higher public score, 67.66 versus 48.08, and the 90% score intervals do not overlap. 5 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Google logo
Gemini 3.7 Flash

Google

67.66/100

Supported · Public rank #19

90% interval 63.0–72.3

Model B
MiniMax logo
MiniMax M2.7

MiniMax

48.08/100

Supported · Public rank #83

90% interval 37.2–58.9

Shared results
5
Gemini 3.7 Flash only
20
MiniMax M2.7 only
18
Like-for-like categories
3 / 8
Supported: Gemini 3.7 Flash and MiniMax M2.7How the comparison works

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.

  • Coding work

    Code generation, repair, and software-engineering tasks

    Gemini 3.7 Flash

    Gemini 3.7 Flash leads on the public coding lane, 60.3 to 36.1, with Supported evidence for both models and non-overlapping 90% intervals.

    Confidence: stronger

  • Agentic work

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

    Gemini 3.7 Flash

    Gemini 3.7 Flash leads on the public agentic lane, 58.6 to 25.2, with Supported evidence for both models and non-overlapping 90% intervals.

    Confidence: stronger

  • Long documents

    Prompts that approach the documented context limit

    Gemini 3.7 Flash

    Gemini 3.7 Flash has the larger documented context window.

    Confidence: documented
Show secondary and unsupported calls

  • Chat turn cost

    1K fresh input + 500 output tokens

    MiniMax M2.7

    MiniMax M2.7 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Repository review cost

    50K fresh input + 3K output tokens

    MiniMax M2.7

    MiniMax M2.7 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

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. MiniMax M2.7 does not fit this workload in one request. MiniMax M2.7 has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

60.3Gemini 3.7 Flash36.1MiniMax M2.7

Like-for-like · BenchAlign v5.7

Gemini 3.7 Flash leads the like-for-like coding row.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboardShortlist models for this job
Same basis rules as the category table below

What is actually comparable

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

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.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.7 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Like-for-like
Gemini 3.7 Flash
58.6
Supported · #20/105
MiniMax M2.7
25.2
Supported · #79/105
Basis
BenchAlign v5.7 lane · 7 vs 7 public rows
Reading
Gemini 3.7 Flash leads

Coding

Like-for-like
Gemini 3.7 Flash
60.3
Supported · #17/135
MiniMax M2.7
36.1
Supported · #70/135
Basis
BenchAlign v5.7 lane · 6 vs 11 public rows
Reading
Gemini 3.7 Flash leads

Knowledge

Like-for-like
Gemini 3.7 Flash
71.1
Supported · #10/158
MiniMax M2.7
43.0
Supported · #79/158
Basis
BenchAlign v5.7 lane · 6 vs 4 public rows
Reading
Gemini 3.7 Flash leads

Reasoning

Not comparable
Gemini 3.7 Flash
77.8
Unranked · 5 rankable rows
MiniMax M2.7
75.9
Unranked · 2 rankable rows
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.7 Flash
82.6
#10/50
MiniMax M2.7
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.7 Flash
Not ranked
MiniMax M2.7
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.7 Flash
Not ranked
MiniMax M2.7
91.6
#10/124
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.7 Flash
Not ranked
MiniMax M2.7
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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 M2.7
$0.0009
Fits in one request

MiniMax M2.7 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 M2.7
$0.0186
Fits in one request

MiniMax M2.7 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
$0.0675
Fits in one request
MiniMax M2.7
$0.078
Does not fit in one request
Cached input priced at the published list-input rate

MiniMax M2.7 does not fit this workload in one request. MiniMax M2.7 has no published cached-input rate, so cached tokens use its listed input rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

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

$0.075 per 1M cached input tokens

Google Gemini API pricing

MiniMax M2.7

Not published

Provider availability

Gemini 3.7 Flash

Generally Available · Gemini API, Google AI Studio, Gemini App - Spark, Gemini Enterprise App, Gemini Enterprise Agent Platform, Google Antigravity

Google DeepMind Gemini 3.7 Flash model card

MiniMax M2.7

Not sourced

Reasoning profile

Gemini 3.7 Flash

Reasoning

MiniMax M2.7

Non-Reasoning

Weight access

Gemini 3.7 Flash

Proprietary

MiniMax M2.7

Open Weight

License

Gemini 3.7 Flash

Proprietary

MiniMax M2.7

Open Weight

Release date

Gemini 3.7 Flash

2026-08-13

MiniMax M2.7

2026-03-18

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
Gemini 3.7 Flash has the higher public score, 67.66 versus 48.08, and the 90% score intervals do not overlap.
Workload cost
Repository review: $0.04875 vs $0.0186. Cache-heavy agent loop: $0.0675 vs $0.078.
Context tradeoff
Gemini 3.7 Flash has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Gemini 3.7 Flash or MiniMax M2.7?

Gemini 3.7 Flash has the higher public score, 67.66 versus 48.08, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Gemini 3.7 Flash or MiniMax M2.7?

Gemini 3.7 Flash leads the public coding lane, 60.3 to 36.1, with Supported evidence for both models and non-overlapping 90% intervals.

Which is better for agentic tasks, Gemini 3.7 Flash or MiniMax M2.7?

Gemini 3.7 Flash leads the public agentic tasks lane, 58.6 to 25.2, with Supported evidence for both models and non-overlapping 90% intervals.

Which costs less, Gemini 3.7 Flash or MiniMax M2.7?

For the stated presets, chat costs $0.00263 on Gemini 3.7 Flash and $0.0009 on MiniMax M2.7; repository review costs $0.04875 and $0.0186; the cache-heavy agent loop costs $0.0675 and $0.078. MiniMax M2.7 does not fit this workload in one request. MiniMax M2.7 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 M2.7?

Gemini 3.7 Flash has the larger documented context window: 1M, compared with 200K.

Benchmark evidence

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

Browse raw public benchmark evidence43 rows

Agentic

  • Terminal-Bench 2.1

    Gemini 3.7 Flash85.8%
    Source
    MiniMax M2.7—

    Not directly comparable

  • Terminal-Bench 3.0

    Gemini 3.7 Flash14.9%
    Source
    MiniMax M2.7—

    Not directly comparable

  • AutomationBench

    Gemini 3.7 Flash30.4%
    Source
    MiniMax M2.7—

    Not directly comparable

  • OSWorld 2.0

    Gemini 3.7 Flash47.9%
    Source
    MiniMax M2.7—

    Not directly comparable

  • Agents' Last Exam

    Gemini 3.7 Flash26.3%
    Source
    MiniMax M2.7—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.7 Flash77.5%
    Source
    MiniMax M2.748.7%
    Source

    Gemini 3.7 Flash leads this result

  • ApprenticeBench

    Gemini 3.7 Flash16%
    Source
    MiniMax M2.7—

    Not directly comparable

  • Terminal-Bench 2.0

    Gemini 3.7 Flash—
    MiniMax M2.757%
    Source

    Not directly comparable

  • Toolathlon

    Gemini 3.7 Flash—
    MiniMax M2.746.3%
    Source

    Not directly comparable

  • MLE-Bench Lite

    Gemini 3.7 Flash—
    MiniMax M2.766.6%
    Source

    Not directly comparable

  • MM-ClawBench

    Gemini 3.7 Flash—
    MiniMax M2.762.7%
    Source

    Not directly comparable

  • Claw-Eval

    Gemini 3.7 Flash—
    MiniMax M2.748.7%
    Source

    Not directly comparable

  • Gert Labs

    Gemini 3.7 Flash—
    MiniMax M2.740.40%
    Source

    Not directly comparable

Coding

  • FrontierCode 1.1 Main

    Gemini 3.7 Flash43.6%
    Source
    MiniMax M2.7—

    Not directly comparable

  • DeepSWE

    Gemini 3.7 Flash65.3%
    Source
    MiniMax M2.7—

    Not directly comparable

  • Terminal-Bench 2.1

    Gemini 3.7 Flash85.8%
    Source
    MiniMax M2.7—

    Not directly comparable

  • FrontierSWE v2

    Gemini 3.7 Flash20.3%
    Source
    MiniMax M2.7—

    Not directly comparable

  • LiveCodeBench (Vals)

    Gemini 3.7 Flash88.7%
    Source
    MiniMax M2.779.9%
    Source

    Gemini 3.7 Flash leads this result

  • SWE-bench (Vals)

    Gemini 3.7 Flash80.8%
    Source
    MiniMax M2.773.8%
    Source

    Gemini 3.7 Flash leads this result

  • SWE-bench Verified*

    Gemini 3.7 Flash—
    MiniMax M2.775.4%
    Source

    Not directly comparable

  • SWE-bench Pro

    Gemini 3.7 Flash—
    MiniMax M2.756.2%
    Source

    Not directly comparable

  • SWE-Rebench

    Gemini 3.7 Flash—
    MiniMax M2.751.9%
    Source

    Not directly comparable

  • SWE Multilingual

    Gemini 3.7 Flash—
    MiniMax M2.776.5%
    Source

    Not directly comparable

  • Multi-SWE Bench

    Gemini 3.7 Flash—
    MiniMax M2.752.7%
    Source

    Not directly comparable

  • VIBE-Pro

    Gemini 3.7 Flash—
    MiniMax M2.755.6%
    Source

    Not directly comparable

  • NL2Repo

    Gemini 3.7 Flash—
    MiniMax M2.739.8%
    Source

    Not directly comparable

  • Vibe Code Bench

    Gemini 3.7 Flash—
    MiniMax M2.727.04%
    Source

    Not directly comparable

  • React Native Evals

    Gemini 3.7 Flash—
    MiniMax M2.771.4%
    Source

    Not directly comparable

Reasoning

  • MRCR v2 64K-128K

    Gemini 3.7 Flash97%
    Source
    MiniMax M2.7—

    Not directly comparable

  • ARC-AGI-1

    Gemini 3.7 Flash95.50%
    Source
    MiniMax M2.7—

    Not directly comparable

  • ARC-AGI-2

    Gemini 3.7 Flash84.6%
    Source
    MiniMax M2.7—

    Not directly comparable

Multimodal

  • CharXiv w/o tools

    Gemini 3.7 Flash84.5%
    Source
    MiniMax M2.7—

    Not directly comparable

  • CharXiv

    Gemini 3.7 Flash88.7%
    Source
    MiniMax M2.7—

    Not directly comparable

  • LVBench

    Gemini 3.7 Flash85.4%
    Source
    MiniMax M2.7—

    Not directly comparable

Knowledge

  • HLE-Verified

    Gemini 3.7 Flash53.6%
    Source
    MiniMax M2.7—

    Not directly comparable

  • LABBench2

    Gemini 3.7 Flash82.1%
    Source
    MiniMax M2.7—

    Not directly comparable

  • BioMysteryBench (human-solvable)

    Gemini 3.7 Flash87.1%
    Source
    MiniMax M2.7—

    Not directly comparable

  • BioMysteryBench (human-difficult)

    Gemini 3.7 Flash43.5%
    Source
    MiniMax M2.7—

    Not directly comparable

  • GPQA Diamond (Vals)

    Gemini 3.7 Flash93.9%
    Source
    MiniMax M2.786.6%
    Source

    Gemini 3.7 Flash leads this result

  • MMLU-Pro (Vals)

    Gemini 3.7 Flash90.1%
    Source
    MiniMax M2.780.4%
    Source

    Gemini 3.7 Flash leads this result

  • GPQA-D

    Gemini 3.7 Flash—
    MiniMax M2.787.0%
    Source

    Not directly comparable

  • MMLU-Pro (Arcee)

    Gemini 3.7 Flash—
    MiniMax M2.780.8%
    Source

    Not directly comparable

Math

  • AIME25 (Arcee)

    Gemini 3.7 Flash—
    MiniMax M2.780.0%
    Source

    Not directly comparable

43 public results · 5 shared

Related comparisons

Compare API pricingRead the methodologyOpen the model selector

Watch Gemini 3.7 Flash vs MiniMax M2.7

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.

Last updated September 27, 2026