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BenchLM
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Model A
Qwen3.5 397B

Alibaba

54.7/100

Estimated · Public rank #100

90% interval 43.2–66.2

Qwen3.5 397B vs Qwen3-Omni-30B-A3B-Instruct

Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Alibaba logo
Model B
Qwen3-Omni-30B-A3B-Instruct

Alibaba

38.33/100

Estimated · Public rank #200

90% interval 26.8–49.8

Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

0 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-Omni-30B-A3B-Instruct is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    Qwen3-Omni-30B-A3B-Instruct is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    Not enough matched evidence

    A complete context comparison is not sourced.

    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. Qwen3.5 397B does not fit this workload in one request. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate. Qwen3-Omni-30B-A3B-Instruct 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
0
Qwen3.5 397B only
38
Qwen3-Omni-30B-A3B-Instruct only
0
Like-for-like categories
0 / 8

2 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

Directional only
Qwen3.5 397B
50.2
Estimated · #77/183
Qwen3-Omni-30B-A3B-Instruct
38.7
Estimated · #142/183
Basis
BenchAlign lane · 6 vs 0 public rows
Reading
Directional only

Instruction following

Directional only
Qwen3.5 397B
0.0
#123/123
Qwen3-Omni-30B-A3B-Instruct
35.2
#112/123
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Directional only

Agentic

Not comparable
Qwen3.5 397B
46.8
Estimated · #71/152
Qwen3-Omni-30B-A3B-Instruct
Not ranked
Basis
BenchAlign lane · 13 vs 0 public rows
Reading
Not comparable

Coding

Not comparable
Qwen3.5 397B
50.2
Estimated · #59/151
Qwen3-Omni-30B-A3B-Instruct
Not ranked
Basis
BenchAlign lane · 3 vs 0 public rows
Reading
Not comparable

Reasoning

Not comparable
Qwen3.5 397B
59.8
Unranked · 2 rankable rows
Qwen3-Omni-30B-A3B-Instruct
21.0
Unranked · 2 rankable rows
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Qwen3.5 397B
74.2
Unranked · 5 rankable rows
Qwen3-Omni-30B-A3B-Instruct
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Qwen3.5 397B
69.7
#5/12
Qwen3-Omni-30B-A3B-Instruct
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Qwen3.5 397B
63.0
#27/48
Qwen3-Omni-30B-A3B-Instruct
41.8
Unranked · 1 rankable row
Basis
Provisional lane · 2 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.

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

Qwen3.5 397B
$0.0024
Fits in one request
Qwen3-Omni-30B-A3B-Instruct
API rate not published
Fit state unavailable

Qwen3-Omni-30B-A3B-Instruct has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Qwen3.5 397B
$0.0408
Fits in one request
Qwen3-Omni-30B-A3B-Instruct
API rate not published
Fit state unavailable

Qwen3-Omni-30B-A3B-Instruct has no comparable published API token rate.

Cache-heavy agent loop

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

Qwen3.5 397B
$0.168
Does not fit in one request
Cached input priced at the published list-input rate
Qwen3-Omni-30B-A3B-Instruct
API rate not published
Fit state unavailable
Cached-input rate unavailable

Qwen3.5 397B does not fit this workload in one request. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate. Qwen3-Omni-30B-A3B-Instruct 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.

Qwen3.5 397B

128K

Qwen3-Omni-30B-A3B-Instruct

N/A

API model ID

Qwen3.5 397B

Not sourced

Qwen3-Omni-30B-A3B-Instruct

Not sourced

Cached-input rate

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

Qwen3.5 397B

Not published

Qwen3-Omni-30B-A3B-Instruct

No comparable hosted API rate

Alibaba model documentation

Documented inputs

Qwen3.5 397B

Not sourced

Qwen3-Omni-30B-A3B-Instruct

Not sourced

Documented outputs

Qwen3.5 397B

Not sourced

Qwen3-Omni-30B-A3B-Instruct

Not sourced

Provider availability

Qwen3.5 397B

Not sourced

Qwen3-Omni-30B-A3B-Instruct

Not sourced

Reasoning profile

Qwen3.5 397B

Non-Reasoning

Qwen3-Omni-30B-A3B-Instruct

Non-Reasoning

Weight access

Qwen3.5 397B

Open Weight

Qwen3-Omni-30B-A3B-Instruct

Open Weight

License

Qwen3.5 397B

Open Weight

Qwen3-Omni-30B-A3B-Instruct

Open Weight

Release date

Qwen3.5 397B

2026-02-16

Qwen3-Omni-30B-A3B-Instruct

2025-09-22

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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
A complete documented context comparison is not available.

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 evidence38 rows

Agentic

  • Terminal-Bench 2.0

    Qwen3.5 397B52.5%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • BrowseComp

    Qwen3.5 397B62%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • Claw-Eval

    Qwen3.5 397B56.8%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • QwenClawBench

    Qwen3.5 397B51.8%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • τ³-bench results

    Qwen3.5 397B68.4%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • VITA-Bench

    Qwen3.5 397B43.7%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • DeepPlanning

    Qwen3.5 397B37.6%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • Toolathlon

    Qwen3.5 397B36.3%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • MCP Atlas

    Qwen3.5 397B46.1%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • MCP-Tasks

    Qwen3.5 397B74.2%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • WideResearch

    Qwen3.5 397B74.0%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • Gert Labs

    Qwen3.5 397B46.76%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • ResearchClawBench

    Qwen3.5 397B14.2%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

Coding

  • SWE-bench Verified

    Qwen3.5 397B76.2%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • LiveCodeBench v6

    Qwen3.5 397B83.6%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • SWE-bench Pro

    Qwen3.5 397B50.9%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

Reasoning

  • LongBench v2

    Qwen3.5 397B63.2%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • AI-Needle

    Qwen3.5 397B68.7%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

Knowledge

  • GPQA

    Qwen3.5 397B88.4%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • SuperGPQA

    Qwen3.5 397B70.4%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • MMLU-Pro

    Qwen3.5 397B87.8%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • MMLU-Redux

    Qwen3.5 397B94.9%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • C-Eval

    Qwen3.5 397B93%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • HLE

    Qwen3.5 397B28.7%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

Math

  • AIME26

    Qwen3.5 397B93.3%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • HMMT Feb 2025

    Qwen3.5 397B94.8%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • HMMT Nov 2025

    Qwen3.5 397B92.7%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • HMMT Feb 2026

    Qwen3.5 397B87.9%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • MMAnswerBench

    Qwen3.5 397B80.9%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

Multilingual

  • MMLU-ProX

    Qwen3.5 397B84.7%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • NOVA-63

    Qwen3.5 397B59.1%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

Multimodal

  • MMMU-Pro

    Qwen3.5 397B79%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • MathVision

    Qwen3.5 397B88.6%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • CharXiv

    Qwen3.5 397B80.8%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • VideoMMMU

    Qwen3.5 397B84.7%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • ScreenSpot Pro

    Qwen3.5 397B65.6%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

  • V*

    Qwen3.5 397B95.8%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

Instruction following

  • IFEval

    Qwen3.5 397B92.6%
    Source
    Qwen3-Omni-30B-A3B-Instruct—

    Not directly comparable

Frequently asked questions

Which is better, Qwen3.5 397B or Qwen3-Omni-30B-A3B-Instruct?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Qwen3.5 397B or Qwen3-Omni-30B-A3B-Instruct?

Qwen3-Omni-30B-A3B-Instruct is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Qwen3.5 397B or Qwen3-Omni-30B-A3B-Instruct?

Qwen3-Omni-30B-A3B-Instruct is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Qwen3.5 397B or Qwen3-Omni-30B-A3B-Instruct?

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, Qwen3.5 397B or Qwen3-Omni-30B-A3B-Instruct?

A complete documented context-window comparison is not available.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 10, 2026

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