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Model comparison

Kimi K2.6 vs Qwen 3.6 Max (preview)

Updated August 7, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Kimi K2.6

Moonshot AI

59.0/100

Estimated · Public rank #62

90% interval 49.1–68.9

Qwen 3.6 Max (preview)

Alibaba

59.4/100

Supported · Public rank #59

90% interval 40.6–78.2

Qwen 3.6 Max (preview) has the higher public score estimate, 59.4 versus 59, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

6 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.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    The category averages use different weighted benchmark sets, so they are 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

  • 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

    A complete comparable API-rate estimate is not available for both models.

    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
6
Kimi K2.6 only
26
Qwen 3.6 Max (preview) only
3
Like-for-like categories
0 / 8

3 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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

Directional only
Kimi K2.6
73.5
Qwen 3.6 Max (preview)
65.4
Weighted basis
3 vs 1 rows
Reading
Directional only

Coding

Directional only
Kimi K2.6
64.4
Qwen 3.6 Max (preview)
51.0
Weighted basis
3 vs 2 rows
Reading
Directional only

Math

Directional only
Kimi K2.6
67.1
Qwen 3.6 Max (preview)
18.4
Weighted basis
4 vs 2 rows
Reading
Directional only

Reasoning

Not comparable
Kimi K2.6
Not measured
Qwen 3.6 Max (preview)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Kimi K2.6
42.2
Qwen 3.6 Max (preview)
73.9
Weighted basis
2 vs 1 rows
Reading
Not comparable

Multilingual

Not comparable
Kimi K2.6
Not measured
Qwen 3.6 Max (preview)
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Kimi K2.6
79.8
Qwen 3.6 Max (preview)
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Kimi K2.6
Not measured
Qwen 3.6 Max (preview)
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.

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

Kimi K2.6
$0.00295
Fits in one request
Qwen 3.6 Max (preview)
API rate not published
Fits in one request

Qwen 3.6 Max (preview) has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Kimi K2.6
$0.0595
Fits in one request
Qwen 3.6 Max (preview)
API rate not published
Fits in one request

Qwen 3.6 Max (preview) has no comparable published API token rate.

Cache-heavy agent loop

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

Kimi K2.6
$0.249
Fits in one request
Cached input priced at the published list-input rate
Qwen 3.6 Max (preview)
API rate not published
Fits in one request
Cached-input rate unavailable

Kimi K2.6 has no published cached-input rate, so cached tokens use its listed input rate. Qwen 3.6 Max (preview) 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.

Kimi K2.6

256K

Qwen 3.6 Max (preview)

256K

API model ID

Kimi K2.6

Not sourced

Qwen 3.6 Max (preview)

Not sourced

Cached-input rate

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

Kimi K2.6

Not published

Qwen 3.6 Max (preview)

No comparable hosted API rate

Documented inputs

Kimi K2.6

Not sourced

Qwen 3.6 Max (preview)

Not sourced

Documented outputs

Kimi K2.6

Not sourced

Qwen 3.6 Max (preview)

Not sourced

Provider availability

Kimi K2.6

Not sourced

Qwen 3.6 Max (preview)

Not sourced

Reasoning profile

Kimi K2.6

Reasoning

Qwen 3.6 Max (preview)

Reasoning

Weight access

Kimi K2.6

Open Weight

Qwen 3.6 Max (preview)

Proprietary

License

Kimi K2.6

Open Weight

Qwen 3.6 Max (preview)

Proprietary

Release date

Kimi K2.6

2026-04-20

Qwen 3.6 Max (preview)

2026-04-20

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
Qwen 3.6 Max (preview) has the higher public score estimate, 59.4 versus 59, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Both models list 256K.

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

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Kimi K2.6
API / mo$3,713
Self-host / mo$18,221
Break-even326M/day
Qwen 3.6 Max (preview)
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Model the full break-even

Benchmark evidence

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

Browse raw public benchmark evidence35 rows

Agentic

  • Terminal-Bench 2.0

    Kimi K2.666.7%
    Source
    Qwen 3.6 Max (preview)65.4%
    Source

    Kimi K2.6 leads this result

  • BrowseComp

    Kimi K2.683.2%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • OSWorld-Verified

    Kimi K2.673.1%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • Toolathlon

    Kimi K2.650%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • MCP Atlas

    Kimi K2.655.9%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • Claw-Eval

    Kimi K2.662.3%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • DeepSearchQA

    Kimi K2.692.5%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • WideResearch

    Kimi K2.680.8%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • Gert Labs

    Kimi K2.656.82%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • ResearchClawBench

    Kimi K2.618.0%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • OSWorld 2.0

    Kimi K2.64.6%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • QwenClawBench

    Kimi K2.6—
    Qwen 3.6 Max (preview)59.0%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Kimi K2.680.2%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • LiveCodeBench v6

    Kimi K2.689.6%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • SWE-bench Pro

    Kimi K2.658.6%
    Source
    Qwen 3.6 Max (preview)57.3%
    Source

    Kimi K2.6 leads this result

  • SWE Multilingual

    Kimi K2.676.7%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • SciCode

    Kimi K2.652.2%
    Source
    Qwen 3.6 Max (preview)47%
    Source

    Kimi K2.6 leads this result

  • Terminal-Bench 2.0

    Kimi K2.666.7%
    Source
    Qwen 3.6 Max (preview)65.4%
    Source

    Kimi K2.6 leads this result

  • Vibe Code Bench

    Kimi K2.637.89%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • cursorBench31

    Kimi K2.647.6%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • NL2Repo

    Kimi K2.6—
    Qwen 3.6 Max (preview)42.9%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Kimi K2.690.5%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • GPQA-D

    Kimi K2.690.5%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • HLE

    Kimi K2.634.7%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • SuperGPQA

    Kimi K2.6—
    Qwen 3.6 Max (preview)73.9%
    Source

    Not directly comparable

Math

  • AIME26

    Kimi K2.696.4%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • HMMT Feb 2026

    Kimi K2.692.7%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • MMAnswerBench

    Kimi K2.686.0%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    Kimi K2.638.966%
    Qwen 3.6 Max (preview)23.103%

    Kimi K2.6 leads this result

  • FrontierMath v2 (Tier 4)

    Shared source
    Kimi K2.614.580%
    Qwen 3.6 Max (preview)4.167%

    Kimi K2.6 leads this result

Multimodal

  • MMMU-Pro

    Kimi K2.679.4%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • MMMU-Pro w/ Python

    Kimi K2.680.1%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • CharXiv

    Kimi K2.680.4%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • MathVision

    Kimi K2.687.4%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

  • V*

    Kimi K2.696.9%
    Source
    Qwen 3.6 Max (preview)—

    Not directly comparable

Frequently asked questions

Which is better, Kimi K2.6 or Qwen 3.6 Max (preview)?

Qwen 3.6 Max (preview) has the higher public score estimate, 59.4 versus 59, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Kimi K2.6 or Qwen 3.6 Max (preview)?

The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Kimi K2.6 or Qwen 3.6 Max (preview)?

The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Kimi K2.6 or Qwen 3.6 Max (preview)?

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, Kimi K2.6 or Qwen 3.6 Max (preview)?

Both models list the same context window, 256K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 7, 2026

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