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BenchLM
Google logo
Model A
Gemini 3.6 Flash

Google

70.11/100

Supported · Public rank #21

90% interval 63.7–75.9

Gemini 3.6 Flash vs MiniMax M3

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

MiniMax logo
Model B
MiniMax M3

MiniMax

63.91/100

Supported · Public rank #51

90% interval 56.5–71.3

Decision reading

Gemini 3.6 Flash has the higher public score estimate, 70.11 versus 63.91, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

6 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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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.

  • Agentic work

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

    Gemini 3.6 Flash

    Gemini 3.6 Flash leads on the public agentic lane, 50.7 to 43.2, with Supported evidence for both models, although the 90% intervals overlap.

    Confidence: limited

  • 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. Costs use the listed standard API rates.

    Confidence: listed-rates

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

    MiniMax M3 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    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
6
Gemini 3.6 Flash only
2
MiniMax M3 only
21
Like-for-like categories
2 / 8

1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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 3.6 Flash
50.7
Supported · #60/151
MiniMax M3
43.2
Supported · #106/151
Basis
BenchAlign lane · 2 vs 9 public rows
Reading
Gemini 3.6 Flash leads · intervals overlap

Knowledge

Like-for-like
Gemini 3.6 Flash
68.6
Supported · #18/181
MiniMax M3
53.8
Supported · #64/181
Basis
BenchAlign lane · 2 vs 2 public rows
Reading
Gemini 3.6 Flash leads · intervals overlap

Coding

Directional only
Gemini 3.6 Flash
58.9
Supported · #30/183
MiniMax M3
50.6
Estimated · #68/183
Basis
BenchAlign lane · 4 vs 10 public rows
Reading
Directional only

Reasoning

Not comparable
Gemini 3.6 Flash
77.8
Unranked · 2 rankable rows
MiniMax M3
78.5
#5/22
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.6 Flash
Not ranked
MiniMax M3
Not ranked
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.6 Flash
Not ranked
MiniMax M3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.6 Flash
82.3
Unranked · 1 rankable row
MiniMax M3
51.5
#34/48
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.6 Flash
Not ranked
MiniMax M3
93.5
#4/120
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) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

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

Gemini 3.6 Flash
$0.00525
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 3.6 Flash
$0.0975
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 3.6 Flash
$0.135
Fits in one request
MiniMax M3
$0.03
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

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 3.6 Flash

$0.15 per 1M cached input tokens

Google Gemini API pricing

MiniMax M3

$0.06 per 1M cached input tokens

Reasoning profile

Gemini 3.6 Flash

Reasoning

MiniMax M3

Non-Reasoning

Weight access

Gemini 3.6 Flash

Proprietary

MiniMax M3

Open Weight

License

Gemini 3.6 Flash

Proprietary

MiniMax M3

Open Weight

Release date

Gemini 3.6 Flash

2026-07-21

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
Gemini 3.6 Flash has the higher public score estimate, 70.11 versus 63.91, but the 90% score intervals overlap.
Workload cost
Repository review: $0.0975 vs $0.0186. Cache-heavy agent loop: $0.135 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 evidence29 rows

Agentic

  • OSWorld-Verified

    Gemini 3.6 Flash83%
    Source
    MiniMax M370.1%
    Source

    Gemini 3.6 Flash leads this result

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.6 Flash73.8%
    Source
    MiniMax M353.6%
    Source

    Gemini 3.6 Flash leads this result

  • Terminal-Bench 2.0

    Gemini 3.6 Flash—
    MiniMax M366%
    Source

    Not directly comparable

  • BrowseComp

    Gemini 3.6 Flash—
    MiniMax M383.5%
    Source

    Not directly comparable

  • MCP Atlas

    Gemini 3.6 Flash—
    MiniMax M374.2%
    Source

    Not directly comparable

  • Claw-Eval

    Gemini 3.6 Flash—
    MiniMax M374.5%
    Source

    Not directly comparable

  • BankerToolBench

    Gemini 3.6 Flash—
    MiniMax M376.1%
    Source

    Not directly comparable

  • ResearchClawBench

    Gemini 3.6 Flash—
    MiniMax M319.8%
    Source

    Not directly comparable

  • OSWorld 2.0

    Gemini 3.6 Flash—
    MiniMax M34.6%
    Source

    Not directly comparable

Coding

  • deepSwe

    Gemini 3.6 Flash49%
    Source
    MiniMax M3—

    Not directly comparable

  • cursorBench32

    Gemini 3.6 Flash53.5%
    Source
    MiniMax M3—

    Not directly comparable

  • LiveCodeBench (Vals)

    Gemini 3.6 Flash88.1%
    Source
    MiniMax M382.2%
    Source

    Gemini 3.6 Flash leads this result

  • SWE-bench (Vals)

    Gemini 3.6 Flash79.6%
    Source
    MiniMax M375.0%
    Source

    Gemini 3.6 Flash leads this result

  • SWE-bench Verified

    Gemini 3.6 Flash—
    MiniMax M380.5%
    Source

    Not directly comparable

  • SWE-bench Pro

    Gemini 3.6 Flash—
    MiniMax M359%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Gemini 3.6 Flash—
    MiniMax M366.0%
    Source

    Not directly comparable

  • NL2Repo

    Gemini 3.6 Flash—
    MiniMax M342.1%
    Source

    Not directly comparable

  • VIBE V2

    Gemini 3.6 Flash—
    MiniMax M350.1%
    Source

    Not directly comparable

  • SVG-Bench

    Gemini 3.6 Flash—
    MiniMax M363.7%
    Source

    Not directly comparable

  • KernelBench Hard

    Gemini 3.6 Flash—
    MiniMax M328.8%
    Source

    Not directly comparable

  • OpenHarmony Bench

    Gemini 3.6 Flash—
    MiniMax M348.4%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Gemini 3.6 Flash93.4%
    Source
    MiniMax M392.7%
    Source

    Gemini 3.6 Flash leads this result

  • MMLU-Pro (Vals)

    Gemini 3.6 Flash89.3%
    Source
    MiniMax M384.2%
    Source

    Gemini 3.6 Flash leads this result

Math

  • USAMO 2026

    Gemini 3.6 Flash—
    MiniMax M385.7%
    Source

    Not directly comparable

Multimodal

  • OfficeQA Pro

    Gemini 3.6 Flash—
    MiniMax M345.1%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Gemini 3.6 Flash—
    MiniMax M391.6%
    Source

    Not directly comparable

  • MMMU-Pro

    Gemini 3.6 Flash—
    MiniMax M378.1%
    Source

    Not directly comparable

  • VideoMMMU

    Gemini 3.6 Flash—
    MiniMax M384.6%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Gemini 3.6 Flash—
    MiniMax M385.4%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3.6 Flash or MiniMax M3?

Gemini 3.6 Flash has the higher public score estimate, 70.11 versus 63.91, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Gemini 3.6 Flash or MiniMax M3?

Gemini 3.6 Flash scores higher for coding on the public lane, 58.9 to 50.6. MiniMax M3 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Gemini 3.6 Flash or MiniMax M3?

Gemini 3.6 Flash leads the public agentic tasks lane, 50.7 to 43.2, with Supported evidence for both models, although the 90% intervals overlap.

Which costs less, Gemini 3.6 Flash or MiniMax M3?

For the stated presets, chat costs $0.00525 on Gemini 3.6 Flash and $0.0009 on MiniMax M3; repository review costs $0.0975 and $0.0186; the cache-heavy agent loop costs $0.135 and $0.03. Costs use the listed standard API rates.

Which has the larger context window, Gemini 3.6 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 September 4, 2026

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