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BenchLM
Google logo
Model A
Gemini 3.5 Flash-Lite

Google

60.5/100

Supported · Public rank #72

90% interval 49.0–72.0

Gemini 3.5 Flash-Lite 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

MiniMax M3 has the higher public score estimate, 63.91 versus 60.5, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

9 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.

  • 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

  • Agentic work

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

    Not enough matched evidence

    Gemini 3.5 Flash-Lite is scored on Estimated evidence for agentic, 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
9
Gemini 3.5 Flash-Lite only
1
MiniMax M3 only
18
Like-for-like categories
1 / 8

3 categories rest 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.

Knowledge

Like-for-like
Gemini 3.5 Flash-Lite
53.0
Supported · #71/181
MiniMax M3
53.8
Supported · #64/181
Basis
BenchAlign lane · 2 vs 2 public rows
Reading
MiniMax M3 leads · intervals overlap

Agentic

Directional only
Gemini 3.5 Flash-Lite
43.4
Estimated · #104/151
MiniMax M3
43.2
Supported · #106/151
Basis
BenchAlign lane · 3 vs 9 public rows
Reading
Directional only

Coding

Directional only
Gemini 3.5 Flash-Lite
43.6
Supported · #121/183
MiniMax M3
50.6
Estimated · #68/183
Basis
BenchAlign lane · 4 vs 10 public rows
Reading
Directional only

Multimodal

Directional only
Gemini 3.5 Flash-Lite
76.1
#16/48
MiniMax M3
51.5
#34/48
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Directional only

Reasoning

Not comparable
Gemini 3.5 Flash-Lite
60.8
Unranked · 3 rankable rows
MiniMax M3
78.5
#5/22
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
MiniMax M3
Not ranked
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
MiniMax M3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.5 Flash-Lite
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 3.5 Flash-Lite
$0.00155
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 3.5 Flash-Lite
$0.0225
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 3.5 Flash-Lite
$0.037
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 3.5 Flash-Lite

$0.03 per 1M cached input tokens

Google Gemini API pricing

MiniMax M3

$0.06 per 1M cached input tokens

Reasoning profile

Gemini 3.5 Flash-Lite

Reasoning

MiniMax M3

Non-Reasoning

Weight access

Gemini 3.5 Flash-Lite

Proprietary

MiniMax M3

Open Weight

License

Gemini 3.5 Flash-Lite

Proprietary

MiniMax M3

Open Weight

Release date

Gemini 3.5 Flash-Lite

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
MiniMax M3 has the higher public score estimate, 63.91 versus 60.5, but the 90% score intervals overlap.
Workload cost
Repository review: $0.0225 vs $0.0186. Cache-heavy agent loop: $0.037 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 evidence28 rows

Agentic

  • Terminal-Bench 2.0

    Gemini 3.5 Flash-Lite54%
    Source
    MiniMax M366%
    Source

    MiniMax M3 leads this result

  • OSWorld-Verified

    Gemini 3.5 Flash-Lite74%
    Source
    MiniMax M370.1%
    Source

    Gemini 3.5 Flash-Lite leads this result

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.5 Flash-Lite50.2%
    Source
    MiniMax M353.6%
    Source

    MiniMax M3 leads this result

  • BrowseComp

    Gemini 3.5 Flash-Lite—
    MiniMax M383.5%
    Source

    Not directly comparable

  • MCP Atlas

    Gemini 3.5 Flash-Lite—
    MiniMax M374.2%
    Source

    Not directly comparable

  • Claw-Eval

    Gemini 3.5 Flash-Lite—
    MiniMax M374.5%
    Source

    Not directly comparable

  • BankerToolBench

    Gemini 3.5 Flash-Lite—
    MiniMax M376.1%
    Source

    Not directly comparable

  • ResearchClawBench

    Gemini 3.5 Flash-Lite—
    MiniMax M319.8%
    Source

    Not directly comparable

  • OSWorld 2.0

    Gemini 3.5 Flash-Lite—
    MiniMax M34.6%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.0

    Gemini 3.5 Flash-Lite54.0%
    Source
    MiniMax M366.0%
    Source

    MiniMax M3 leads this result

  • SWE-bench Pro

    Gemini 3.5 Flash-Lite54.2%
    Source
    MiniMax M359%
    Source

    MiniMax M3 leads this result

  • LiveCodeBench (Vals)

    Gemini 3.5 Flash-Lite79.0%
    Source
    MiniMax M382.2%
    Source

    MiniMax M3 leads this result

  • SWE-bench (Vals)

    Gemini 3.5 Flash-Lite75.0%
    Source
    MiniMax M375.0%
    Source

    Tie

  • SWE-bench Verified

    Gemini 3.5 Flash-Lite—
    MiniMax M380.5%
    Source

    Not directly comparable

  • NL2Repo

    Gemini 3.5 Flash-Lite—
    MiniMax M342.1%
    Source

    Not directly comparable

  • VIBE V2

    Gemini 3.5 Flash-Lite—
    MiniMax M350.1%
    Source

    Not directly comparable

  • SVG-Bench

    Gemini 3.5 Flash-Lite—
    MiniMax M363.7%
    Source

    Not directly comparable

  • KernelBench Hard

    Gemini 3.5 Flash-Lite—
    MiniMax M328.8%
    Source

    Not directly comparable

  • OpenHarmony Bench

    Gemini 3.5 Flash-Lite—
    MiniMax M348.4%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    Gemini 3.5 Flash-Lite72.2%
    Source
    MiniMax M3—

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Gemini 3.5 Flash-Lite83.8%
    Source
    MiniMax M392.7%
    Source

    MiniMax M3 leads this result

  • MMLU-Pro (Vals)

    Gemini 3.5 Flash-Lite85.8%
    Source
    MiniMax M384.2%
    Source

    Gemini 3.5 Flash-Lite leads this result

Math

  • USAMO 2026

    Gemini 3.5 Flash-Lite—
    MiniMax M385.7%
    Source

    Not directly comparable

Multimodal

  • OfficeQA Pro

    Gemini 3.5 Flash-Lite—
    MiniMax M345.1%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Gemini 3.5 Flash-Lite—
    MiniMax M391.6%
    Source

    Not directly comparable

  • MMMU-Pro

    Gemini 3.5 Flash-Lite—
    MiniMax M378.1%
    Source

    Not directly comparable

  • VideoMMMU

    Gemini 3.5 Flash-Lite—
    MiniMax M384.6%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Gemini 3.5 Flash-Lite—
    MiniMax M385.4%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3.5 Flash-Lite or MiniMax M3?

MiniMax M3 has the higher public score estimate, 63.91 versus 60.5, 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 3.5 Flash-Lite or MiniMax M3?

MiniMax M3 scores higher for coding on the public lane, 50.6 to 43.6. 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 3.5 Flash-Lite or MiniMax M3?

Gemini 3.5 Flash-Lite scores higher for agentic tasks on the public lane, 43.4 to 43.2. Gemini 3.5 Flash-Lite is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Gemini 3.5 Flash-Lite or MiniMax M3?

For the stated presets, chat costs $0.00155 on Gemini 3.5 Flash-Lite and $0.0009 on MiniMax M3; repository review costs $0.0225 and $0.0186; the cache-heavy agent loop costs $0.037 and $0.03. Costs use the listed standard API rates.

Which has the larger context window, Gemini 3.5 Flash-Lite or MiniMax M3?

Both models list the same context window, 1M.

Related comparisons

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Last updated September 4, 2026

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