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

Updated October 19, 2026. Rank says Qwen3.6-27B is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Qwen3.6-27B has the higher public point estimate, 48.57 versus 43.5. Their conditional score ranges overlap. These ranges do not establish rank confidence. 32 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Qwen3.6-27B

Alibaba

48.57/100

Estimated · Public rank #104

Conditional range 34.2–62.9

Model B

Qwen3.6-35B-A3B

Alibaba

43.5/100

Estimated · Public rank #124

Conditional range 29.1–57.9

Shared results: 32
Qwen3.6-27B only: 8
Qwen3.6-35B-A3B only: 10
Like-for-like categories: 2 / 8

Estimated: Qwen3.6-27B and Qwen3.6-35B-A3B. Conditional ranges do not establish rank confidence.How the comparison works

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

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

34.8Qwen3.6-27B31.5Qwen3.6-35B-A3B

Directional only · BenchAlign v5.8

Qwen3.6-27B has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

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.

FrontierMath v2 (Tiers 1-3)Math
Normalized gap 14.7
Qwen3.6-27B:35.088%
Qwen3.6-35B-A3B:20.351%
Shared source
Terminal-Bench 2.0Agentic
Normalized gap 7.8
Qwen3.6-27B:59.3%
Qwen3.6-35B-A3B:51.5%
Qwen3.6-27B source Qwen3.6-35B-A3B source
SWE MultilingualCoding
Normalized gap 4.1
Qwen3.6-27B:71.3%
Qwen3.6-35B-A3B:67.2%
Qwen3.6-27B source Qwen3.6-35B-A3B source
SWE-bench ProCoding
Normalized gap 4.0
Qwen3.6-27B:53.5%
Qwen3.6-35B-A3B:49.5%
Qwen3.6-27B source Qwen3.6-35B-A3B source
SWE-bench VerifiedCoding
Normalized gap 3.8
Qwen3.6-27B:77.2%
Qwen3.6-35B-A3B:73.4%
Qwen3.6-27B source Qwen3.6-35B-A3B source

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 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: 67.3; #39/55
Qwen3.6-35B-A3B: 66.4; #41/55
Basis: Provisional lane · 2 vs 2 weighted rows
Reading: Qwen3.6-27B leads

Math

Like-for-like

Qwen3.6-27B: 65.9; #8/12
Qwen3.6-35B-A3B: 58.4; #10/12
Basis: Provisional lane · 3 vs 3 weighted rows
Reading: Qwen3.6-27B leads

Agentic

Directional only

Qwen3.6-27B: 29.1; Supported · #97/130
Qwen3.6-35B-A3B: 30.2; Estimated · #96/130
Basis: BenchAlign v5.8 lane · 6 vs 11 public rows
Reading: Directional only

Coding

Directional only

Qwen3.6-27B: 34.8; Supported · #80/151
Qwen3.6-35B-A3B: 31.5; Estimated · #93/151
Basis: BenchAlign v5.8 lane · 7 vs 6 public rows
Reading: Directional only

Knowledge

Directional only

Qwen3.6-27B: 46.8; Estimated · #92/186
Qwen3.6-35B-A3B: 42.8; Estimated · #110/186
Basis: BenchAlign v5.8 lane · 6 vs 5 public rows
Reading: Directional only

Instruction following

Directional only

Qwen3.6-27B: 82.4; #55/148
Qwen3.6-35B-A3B: 78.3; #61/148
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Directional only

Reasoning

Not comparable

Qwen3.6-27B: 78.1; Unranked · 2 rankable rows
Qwen3.6-35B-A3B: 74.3; Unranked · 2 rankable rows
Basis: Provisional lane · 0 vs 0 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

Category scores with the server-provided evidence basis for Qwen3.6-27B and Qwen3.6-35B-A3B
Category	Qwen3.6-27B	Qwen3.6-35B-A3B	Basis	Reading
Multimodal	67.3#39/55	66.4#41/55	Like-for-likeProvisional lane · 2 vs 2 weighted rows	Qwen3.6-27B leads
Math	65.9#8/12	58.4#10/12	Like-for-likeProvisional lane · 3 vs 3 weighted rows	Qwen3.6-27B leads
Agentic	29.1Supported · #97/130	30.2Estimated · #96/130	Directional onlyBenchAlign v5.8 lane · 6 vs 11 public rows	Directional only
Coding	34.8Supported · #80/151	31.5Estimated · #93/151	Directional onlyBenchAlign v5.8 lane · 7 vs 6 public rows	Directional only
Knowledge	46.8Estimated · #92/186	42.8Estimated · #110/186	Directional onlyBenchAlign v5.8 lane · 6 vs 5 public rows	Directional only
Instruction following	82.4#55/148	78.3#61/148	Directional onlyProvisional lane · 0 vs 0 weighted rows	Directional only
Reasoning	78.1Unranked · 2 rankable rows	74.3Unranked · 2 rankable rows	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

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

SpecificationQwen3.6-27BQwen3.6-35B-A3B

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 point estimate, 48.57 versus 43.5. Their conditional score ranges overlap. These ranges do not establish rank confidence.
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.

Questions

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

Qwen3.6-27B has the higher public point estimate, 48.57 versus 43.5. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

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

Qwen3.6-27B scores higher for coding on the public lane, 34.8 to 31.5. 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, 30.2 to 29.1. 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.

Self-host vs API cost

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

Qwen3.6-27B

API / mo$0

Self-host / mo$298

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 evidence50 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 v6
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
SWE-bench (Vals)
Qwen3.6-27B70.0%
Source
Qwen3.6-35B-A3B—
Not directly comparable

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

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
FrontierMath v2 (Tiers 1-3)
Shared source
Qwen3.6-27B35.088%
Qwen3.6-35B-A3B20.351%
Qwen3.6-27B leads this result

50 public results · 32 shared

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Last updated October 19, 2026

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

Decision reading

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Multimodal

Math

Agentic

Coding

Knowledge

Instruction following

Reasoning

Multilingual

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

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

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

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

Which costs less, Qwen3.6-27B or Qwen3.6-35B-A3B?

Which has the larger context window, Qwen3.6-27B or Qwen3.6-35B-A3B?

Self-host vs API cost

Benchmark evidence

Agentic

Coding

Multimodal

Knowledge

Math

Related comparisons

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