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Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.

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Model A
MiniMax M2.5

MiniMax

58.7/100

Supported · Public rank #75

90% interval 50.8–66.6

MiniMax M2.5 vs Qwen3.6 Plus

Updated August 18, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
Qwen3.6 Plus

Alibaba

64.8/100

Supported · Public rank #36

90% interval 55.7–73.9

Decision reading

Qwen3.6 Plus has the higher public score estimate, 64.79 versus 58.68, 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

    Qwen3.6 Plus

    Qwen3.6 Plus 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

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. MiniMax M2.5 does not fit this workload in one request. MiniMax M2.5 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.6 Plus has no comparable published API token rate.

    Confidence: rate-fallback

  • 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.

Shared results
1
MiniMax M2.5 only
0
Qwen3.6 Plus only
43
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
MiniMax M2.5
Not measured
Qwen3.6 Plus
61.6
Weighted basis
0 vs 1 rows
Reading
Not comparable

Coding

Not comparable
MiniMax M2.5
Not measured
Qwen3.6 Plus
70.3
Weighted basis
0 vs 2 rows
Reading
Not comparable

Reasoning

Not comparable
MiniMax M2.5
Not measured
Qwen3.6 Plus
62.0
Weighted basis
0 vs 1 rows
Reading
Not comparable

Knowledge

Not comparable
MiniMax M2.5
Not measured
Qwen3.6 Plus
57.1
Weighted basis
0 vs 4 rows
Reading
Not comparable

Math

Not comparable
MiniMax M2.5
Not measured
Qwen3.6 Plus
60.5
Weighted basis
0 vs 4 rows
Reading
Not comparable

Multilingual

Not comparable
MiniMax M2.5
Not measured
Qwen3.6 Plus
84.7
Weighted basis
0 vs 1 rows
Reading
Not comparable

Multimodal

Not comparable
MiniMax M2.5
Not measured
Qwen3.6 Plus
79.8
Weighted basis
0 vs 2 rows
Reading
Not comparable

Instruction following

Not comparable
MiniMax M2.5
Not measured
Qwen3.6 Plus
82.3
Weighted basis
0 vs 2 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

MiniMax M2.5
$0.0009
Fits in one request
Qwen3.6 Plus
API rate not published
Fits in one request

Qwen3.6 Plus has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

MiniMax M2.5
$0.0186
Fits in one request
Qwen3.6 Plus
API rate not published
Fits in one request

Qwen3.6 Plus has no comparable published API token rate.

Cache-heavy agent loop

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

MiniMax M2.5
$0.078
Does not fit in one request
Cached input priced at the published list-input rate
Qwen3.6 Plus
API rate not published
Fits in one request
Cached-input rate unavailable

MiniMax M2.5 does not fit this workload in one request. MiniMax M2.5 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.6 Plus has no comparable published API token rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Context window

Maximum documented context; output-token limits may be lower.

MiniMax M2.5

128K

Qwen3.6 Plus

1M

API model ID

MiniMax M2.5

Not sourced

Qwen3.6 Plus

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

MiniMax M2.5

Not published

Qwen3.6 Plus

No comparable hosted API rate

Documented inputs

MiniMax M2.5

Not sourced

Qwen3.6 Plus

Not sourced

Documented outputs

MiniMax M2.5

Not sourced

Qwen3.6 Plus

Not sourced

Provider availability

MiniMax M2.5

Not sourced

Qwen3.6 Plus

Not sourced

Reasoning profile

MiniMax M2.5

Non-Reasoning

Qwen3.6 Plus

Reasoning

Weight access

MiniMax M2.5

Proprietary

Qwen3.6 Plus

Proprietary

License

MiniMax M2.5

Proprietary

Qwen3.6 Plus

Proprietary

Release date

MiniMax M2.5

2025-10-01

Qwen3.6 Plus

2026-04-02

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
Qwen3.6 Plus has the higher public score estimate, 64.79 versus 58.68, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Qwen3.6 Plus has the larger documented window (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 evidence44 rows

Agentic

  • Terminal-Bench 2.0

    MiniMax M2.5
    Qwen3.6 Plus61.6%
    Source

    Not directly comparable

  • Claw-Eval

    MiniMax M2.5
    Qwen3.6 Plus58.8%
    Source

    Not directly comparable

  • QwenClawBench

    MiniMax M2.5
    Qwen3.6 Plus57.2%
    Source

    Not directly comparable

  • τ³-bench results

    MiniMax M2.5
    Qwen3.6 Plus70.7%
    Source

    Not directly comparable

  • VITA-Bench

    MiniMax M2.5
    Qwen3.6 Plus44.3%
    Source

    Not directly comparable

  • DeepPlanning

    MiniMax M2.5
    Qwen3.6 Plus41.5%
    Source

    Not directly comparable

  • Toolathlon

    MiniMax M2.5
    Qwen3.6 Plus39.8%
    Source

    Not directly comparable

  • MCP Atlas

    MiniMax M2.5
    Qwen3.6 Plus48.2%
    Source

    Not directly comparable

  • MCP-Tasks

    MiniMax M2.5
    Qwen3.6 Plus74.1%
    Source

    Not directly comparable

  • WideResearch

    MiniMax M2.5
    Qwen3.6 Plus74.3%
    Source

    Not directly comparable

  • Gert Labs

    MiniMax M2.5
    Qwen3.6 Plus50.60%
    Source

    Not directly comparable

  • ResearchClawBench

    MiniMax M2.5
    Qwen3.6 Plus18.0%
    Source

    Not directly comparable

Coding

  • Vibe Code Bench

    Shared source
    MiniMax M2.514.85%
    Qwen3.6 Plus25.56%

    Qwen3.6 Plus leads this result

  • SWE-bench Verified

    MiniMax M2.5
    Qwen3.6 Plus78.8%
    Source

    Not directly comparable

  • SWE-bench Pro

    MiniMax M2.5
    Qwen3.6 Plus56.6%
    Source

    Not directly comparable

  • SWE Multilingual

    MiniMax M2.5
    Qwen3.6 Plus73.8%
    Source

    Not directly comparable

  • LiveCodeBench v6

    MiniMax M2.5
    Qwen3.6 Plus87.1%
    Source

    Not directly comparable

  • EEBench

    MiniMax M2.5
    Qwen3.6 Plus12.7%
    Source

    Not directly comparable

Reasoning

  • AI-Needle

    MiniMax M2.5
    Qwen3.6 Plus68.3%
    Source

    Not directly comparable

  • LongBench v2

    MiniMax M2.5
    Qwen3.6 Plus62%
    Source

    Not directly comparable

Knowledge

  • GPQA

    MiniMax M2.5
    Qwen3.6 Plus90.4%
    Source

    Not directly comparable

  • SuperGPQA

    MiniMax M2.5
    Qwen3.6 Plus71.6%
    Source

    Not directly comparable

  • MMLU-Pro

    MiniMax M2.5
    Qwen3.6 Plus88.5%
    Source

    Not directly comparable

  • MMLU-Redux

    MiniMax M2.5
    Qwen3.6 Plus94.5%
    Source

    Not directly comparable

  • C-Eval

    MiniMax M2.5
    Qwen3.6 Plus93.3%
    Source

    Not directly comparable

  • HLE

    MiniMax M2.5
    Qwen3.6 Plus28.8%
    Source

    Not directly comparable

Math

  • AIME26

    MiniMax M2.5
    Qwen3.6 Plus95.3%
    Source

    Not directly comparable

  • HMMT Feb 2025

    MiniMax M2.5
    Qwen3.6 Plus96.7%
    Source

    Not directly comparable

  • HMMT Nov 2025

    MiniMax M2.5
    Qwen3.6 Plus94.6%
    Source

    Not directly comparable

  • HMMT Feb 2026

    MiniMax M2.5
    Qwen3.6 Plus87.8%
    Source

    Not directly comparable

  • MMAnswerBench

    MiniMax M2.5
    Qwen3.6 Plus83.8%
    Source

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    MiniMax M2.5
    Qwen3.6 Plus26.207%
    Source

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    MiniMax M2.5
    Qwen3.6 Plus8.333%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    MiniMax M2.5
    Qwen3.6 Plus84.7%
    Source

    Not directly comparable

  • NOVA-63

    MiniMax M2.5
    Qwen3.6 Plus57.9%
    Source

    Not directly comparable

Multimodal

  • MMMU

    MiniMax M2.5
    Qwen3.6 Plus86.0%
    Source

    Not directly comparable

  • MMMU-Pro

    MiniMax M2.5
    Qwen3.6 Plus78.8%
    Source

    Not directly comparable

  • MathVision

    MiniMax M2.5
    Qwen3.6 Plus88.0%
    Source

    Not directly comparable

  • VideoMMMU

    MiniMax M2.5
    Qwen3.6 Plus84.0%
    Source

    Not directly comparable

  • ScreenSpot Pro

    MiniMax M2.5
    Qwen3.6 Plus68.2%
    Source

    Not directly comparable

  • CharXiv

    MiniMax M2.5
    Qwen3.6 Plus81.5%
    Source

    Not directly comparable

  • V*

    MiniMax M2.5
    Qwen3.6 Plus96.9%
    Source

    Not directly comparable

Instruction following

  • IFEval

    MiniMax M2.5
    Qwen3.6 Plus94.3%
    Source

    Not directly comparable

  • IFBench

    MiniMax M2.5
    Qwen3.6 Plus75.8%
    Source

    Not directly comparable

Frequently asked questions

Which is better, MiniMax M2.5 or Qwen3.6 Plus?

Qwen3.6 Plus has the higher public score estimate, 64.79 versus 58.68, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, MiniMax M2.5 or Qwen3.6 Plus?

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, MiniMax M2.5 or Qwen3.6 Plus?

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, MiniMax M2.5 or Qwen3.6 Plus?

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, MiniMax M2.5 or Qwen3.6 Plus?

Qwen3.6 Plus has the larger documented context window: 1M, compared with 128K.

Related comparisons

Last updated August 18, 2026

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