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Radar

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

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BenchLM
Alibaba logo
Model A
Qwen3.6-27B

Alibaba

52.73/100

Estimated · Public rank #120

90% interval 47.0–58.5

Qwen3.6-27B vs Qwen3.6-35B-A3B

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

Alibaba logo
Model B
Qwen3.6-35B-A3B

Alibaba

48.34/100

Estimated · Public rank #150

90% interval 42.6–54.1

Decision reading

Qwen3.6-27B has the higher public score estimate, 52.73 versus 48.34, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

31 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.

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

    Qwen3.6-35B-A3B 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

    Qwen3.6-35B-A3B 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

  • 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: listed-rates

  • 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
31
Qwen3.6-27B only
7
Qwen3.6-35B-A3B only
10
Like-for-like categories
1 / 8

4 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.

Multimodal

Like-for-like
Qwen3.6-27B
51.5
#35/48
Qwen3.6-35B-A3B
49.7
#37/48
Basis
Provisional lane · 2 vs 2 weighted rows
Reading
Qwen3.6-27B leads

Agentic

Directional only
Qwen3.6-27B
33.9
Supported · #133/151
Qwen3.6-35B-A3B
44.4
Estimated · #102/151
Basis
BenchAlign lane · 6 vs 11 public rows
Reading
Directional only

Coding

Directional only
Qwen3.6-27B
42.6
Supported · #128/183
Qwen3.6-35B-A3B
47.3
Estimated · #90/183
Basis
BenchAlign lane · 6 vs 6 public rows
Reading
Directional only

Knowledge

Directional only
Qwen3.6-27B
49.0
Estimated · #95/181
Qwen3.6-35B-A3B
46.5
Estimated · #109/181
Basis
BenchAlign lane · 6 vs 5 public rows
Reading
Directional only

Instruction following

Directional only
Qwen3.6-27B
82.2
#50/120
Qwen3.6-35B-A3B
78.0
#55/120
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Directional only

Reasoning

Not comparable
Qwen3.6-27B
73.7
Unranked · 2 rankable rows
Qwen3.6-35B-A3B
69.0
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Qwen3.6-27B
72.8
Unranked · 5 rankable rows
Qwen3.6-35B-A3B
71.5
Unranked · 5 rankable rows
Basis
Provisional lane · 2 vs 2 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Qwen3.6-27B
Not ranked
Qwen3.6-35B-A3B
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) 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

Qwen3.6-27B
Self-hosted; infrastructure cost varies
Fits in one request
Qwen3.6-35B-A3B
API rate not published
Fits in one request

Qwen3.6-27B has no comparable published API token rate. Qwen3.6-35B-A3B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Qwen3.6-27B
Self-hosted; infrastructure cost varies
Fits in one request
Qwen3.6-35B-A3B
API rate not published
Fits in one request

Qwen3.6-27B has no comparable published API token rate. Qwen3.6-35B-A3B has no comparable published API token rate.

Cache-heavy agent loop

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

Qwen3.6-27B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable
Qwen3.6-35B-A3B
API rate not published
Fits in one request
Cached-input rate unavailable

Qwen3.6-27B has no comparable published API token rate. Qwen3.6-35B-A3B 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.

Qwen3.6-27B

262K

Qwen3.6-35B-A3B

262K

API model ID

Qwen3.6-27B

Not sourced

Qwen3.6-35B-A3B

Not sourced

Cached-input rate

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

Qwen3.6-27B

No comparable hosted API rate

Qwen3.6-35B-A3B

No comparable hosted API rate

Documented inputs

Qwen3.6-27B

Not sourced

Qwen3.6-35B-A3B

Not sourced

Documented outputs

Qwen3.6-27B

Not sourced

Qwen3.6-35B-A3B

Not sourced

Provider availability

Qwen3.6-27B

Not sourced

Qwen3.6-35B-A3B

Not sourced

Reasoning profile

Qwen3.6-27B

Reasoning

Qwen3.6-35B-A3B

Reasoning

Weight access

Qwen3.6-27B

Open Weight

Qwen3.6-35B-A3B

Open Weight

License

Qwen3.6-27B

Open Weight

Qwen3.6-35B-A3B

Open Weight

Release date

Qwen3.6-27B

2026-04-21

Qwen3.6-35B-A3B

2026-04-15

If you already use one of these models
Deployment change
Both entries list Alibaba as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
Quality signal
Qwen3.6-27B has the higher public score estimate, 52.73 versus 48.34, 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 262K.

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.

Qwen3.6-27B
API / mo$0
Self-host / mo$429
Break-even—
Qwen3.6-35B-A3B
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 evidence48 rows

Agentic

  • Terminal-Bench 2.0

    Qwen3.6-27B59.3%
    Source
    Qwen3.6-35B-A3B51.5%
    Source

    Qwen3.6-27B leads this result

  • Claw-Eval

    Qwen3.6-27B72.4%
    Source
    Qwen3.6-35B-A3B68.7%
    Source

    Qwen3.6-27B leads this result

  • QwenClawBench

    Qwen3.6-27B53.4%
    Source
    Qwen3.6-35B-A3B52.6%
    Source

    Qwen3.6-27B leads this result

  • QwenWebBench

    Qwen3.6-27B1487
    Source
    Qwen3.6-35B-A3B1397
    Source

    Qwen3.6-27B leads this result

  • AndroidWorld

    Qwen3.6-27B70.3%
    Source
    Qwen3.6-35B-A3B—

    Not directly comparable

  • Gert Labs

    Shared source
    Qwen3.6-27B54.84%
    Qwen3.6-35B-A3B42.65%

    Qwen3.6-27B leads this result

  • τ³-bench results

    Qwen3.6-27B—
    Qwen3.6-35B-A3B67.2%
    Source

    Not directly comparable

  • VITA-Bench

    Qwen3.6-27B—
    Qwen3.6-35B-A3B35.6%
    Source

    Not directly comparable

  • DeepPlanning

    Qwen3.6-27B—
    Qwen3.6-35B-A3B25.9%
    Source

    Not directly comparable

  • Toolathlon

    Qwen3.6-27B—
    Qwen3.6-35B-A3B26.9%
    Source

    Not directly comparable

  • MCP Atlas

    Qwen3.6-27B—
    Qwen3.6-35B-A3B62.8%
    Source

    Not directly comparable

  • WideResearch

    Qwen3.6-27B—
    Qwen3.6-35B-A3B60.1%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Qwen3.6-27B77.2%
    Source
    Qwen3.6-35B-A3B73.4%
    Source

    Qwen3.6-27B leads this result

  • SWE Multilingual

    Qwen3.6-27B71.3%
    Source
    Qwen3.6-35B-A3B67.2%
    Source

    Qwen3.6-27B leads this result

  • SWE-bench Pro

    Qwen3.6-27B53.5%
    Source
    Qwen3.6-35B-A3B49.5%
    Source

    Qwen3.6-27B leads this result

  • Terminal-Bench 2.0

    Qwen3.6-27B59.3%
    Source
    Qwen3.6-35B-A3B51.5%
    Source

    Qwen3.6-27B leads this result

  • LiveCodeBench

    Qwen3.6-27B83.9%
    Source
    Qwen3.6-35B-A3B80.4%
    Source

    Qwen3.6-27B leads this result

  • NL2Repo

    Qwen3.6-27B36.2%
    Source
    Qwen3.6-35B-A3B29.4%
    Source

    Qwen3.6-27B leads this result

Knowledge

  • MMLU-Pro

    Qwen3.6-27B86.2%
    Source
    Qwen3.6-35B-A3B85.2%
    Source

    Qwen3.6-27B leads this result

  • MMLU-Redux

    Qwen3.6-27B93.5%
    Source
    Qwen3.6-35B-A3B—

    Not directly comparable

  • SuperGPQA

    Qwen3.6-27B66%
    Source
    Qwen3.6-35B-A3B64.7%
    Source

    Qwen3.6-27B leads this result

  • C-Eval

    Qwen3.6-27B91.4%
    Source
    Qwen3.6-35B-A3B90%
    Source

    Qwen3.6-27B leads this result

  • GPQA

    Qwen3.6-27B87.8%
    Source
    Qwen3.6-35B-A3B86%
    Source

    Qwen3.6-27B leads this result

  • HLE

    Qwen3.6-27B24%
    Source
    Qwen3.6-35B-A3B21.4%
    Source

    Qwen3.6-27B leads this result

Math

  • HMMT Feb 2025

    Qwen3.6-27B93.8%
    Source
    Qwen3.6-35B-A3B90.7%
    Source

    Qwen3.6-27B leads this result

  • HMMT Nov 2025

    Qwen3.6-27B90.7%
    Source
    Qwen3.6-35B-A3B89.1%
    Source

    Qwen3.6-27B leads this result

  • HMMT Feb 2026

    Qwen3.6-27B84.3%
    Source
    Qwen3.6-35B-A3B83.6%
    Source

    Qwen3.6-27B leads this result

  • MMAnswerBench

    Qwen3.6-27B80.8%
    Source
    Qwen3.6-35B-A3B78.9%
    Source

    Qwen3.6-27B leads this result

  • AIME26

    Qwen3.6-27B94.1%
    Source
    Qwen3.6-35B-A3B92.7%
    Source

    Qwen3.6-27B leads this result

Multimodal

  • MMMU

    Qwen3.6-27B82.9%
    Source
    Qwen3.6-35B-A3B81.7%
    Source

    Qwen3.6-27B leads this result

  • MMMU-Pro

    Qwen3.6-27B75.8%
    Source
    Qwen3.6-35B-A3B75.3%
    Source

    Qwen3.6-27B leads this result

  • RealWorldQA

    Qwen3.6-27B84.1%
    Source
    Qwen3.6-35B-A3B85.3%
    Source

    Qwen3.6-35B-A3B leads this result

  • DynaMath

    Qwen3.6-27B85.6%
    Source
    Qwen3.6-35B-A3B—

    Not directly comparable

  • MStar

    Qwen3.6-27B81.4%
    Source
    Qwen3.6-35B-A3B—

    Not directly comparable

  • SimpleVQA

    Qwen3.6-27B56.1%
    Source
    Qwen3.6-35B-A3B58.9%
    Source

    Qwen3.6-35B-A3B leads this result

  • CharXiv

    Qwen3.6-27B78.4%
    Source
    Qwen3.6-35B-A3B78%
    Source

    Qwen3.6-27B leads this result

  • CC-OCR

    Qwen3.6-27B81.2%
    Source
    Qwen3.6-35B-A3B81.9%
    Source

    Qwen3.6-35B-A3B leads this result

  • CountBench

    Qwen3.6-27B97.8%
    Source
    Qwen3.6-35B-A3B—

    Not directly comparable

  • RefCOCO (avg)

    Qwen3.6-27B92.5%
    Source
    Qwen3.6-35B-A3B92.0%
    Source

    Qwen3.6-27B leads this result

  • ERQA

    Qwen3.6-27B62.5%
    Source
    Qwen3.6-35B-A3B—

    Not directly comparable

  • Video-MME (with subtitle)

    Qwen3.6-27B87.7%
    Source
    Qwen3.6-35B-A3B86.6%
    Source

    Qwen3.6-27B leads this result

  • VideoMMMU

    Qwen3.6-27B84.4%
    Source
    Qwen3.6-35B-A3B83.7%
    Source

    Qwen3.6-27B leads this result

  • MLVU (M-Avg)

    Qwen3.6-27B86.6%
    Source
    Qwen3.6-35B-A3B86.2%
    Source

    Qwen3.6-27B leads this result

  • V*

    Qwen3.6-27B94.7%
    Source
    Qwen3.6-35B-A3B—

    Not directly comparable

  • OmniDocBench 1.5

    Qwen3.6-27B—
    Qwen3.6-35B-A3B89.9%
    Source

    Not directly comparable

  • AI2D_TEST

    Qwen3.6-27B—
    Qwen3.6-35B-A3B92.7%
    Source

    Not directly comparable

  • ODINW13

    Qwen3.6-27B—
    Qwen3.6-35B-A3B50.8%
    Source

    Not directly comparable

  • Video-MME (w/o subtitle)

    Qwen3.6-27B—
    Qwen3.6-35B-A3B82.5%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Qwen3.6-27B or Qwen3.6-35B-A3B?

Qwen3.6-27B has the higher public score estimate, 52.73 versus 48.34, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Qwen3.6-27B or Qwen3.6-35B-A3B?

Qwen3.6-35B-A3B scores higher for coding on the public lane, 47.3 to 42.6. Qwen3.6-35B-A3B 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, Qwen3.6-27B or Qwen3.6-35B-A3B?

Qwen3.6-35B-A3B scores higher for agentic tasks on the public lane, 44.4 to 33.9. Qwen3.6-35B-A3B 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, Qwen3.6-27B or Qwen3.6-35B-A3B?

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, Qwen3.6-27B or Qwen3.6-35B-A3B?

Both models list the same context window, 262K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 4, 2026

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