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Mercury 3 vs Qwen3.5 397B

Updated October 19, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. 2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Inception logo

Inception

—

Evidence status unavailable

90% interval unavailable

Model B
Alibaba logo

Alibaba

55.42/100

Estimated · Public rank #66

Conditional range 41.1–69.8

Shared results
2
Mercury 3 only
6
Qwen3.5 397B only
60
Like-for-like categories
0 / 8
Estimated: Qwen3.5 397B. 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.

  • Long documents

    Prompts that approach the documented context limit

    Mercury 3

    Mercury 3 has the larger documented context window.

    Confidence: documented
  • Chat turn cost

    1K fresh input + 500 output tokens

    Mercury 3

    Mercury 3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
Show secondary and unsupported calls
  • Repository review cost

    50K fresh input + 3K output tokens

    Mercury 3

    Mercury 3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Mercury 3 and Qwen3.5 397B are 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

    Mercury 3 is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited
  • 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.

    Confidence: rate-fallback

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.

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

—Mercury 3—Qwen3.5 397B

Not comparable · BenchAlign v5.8

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

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

Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

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.

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.

Agentic

Not comparable
Mercury 3
Not ranked
Qwen3.5 397B
44.3
Estimated · #62/130
Basis
BenchAlign v5.8 lane · 3 vs 14 public rows
Reading
Not comparable

Coding

Not comparable
Mercury 3
Not ranked
Qwen3.5 397B
Not ranked
Basis
BenchAlign v5.8 lane · 1 vs 6 public rows
Reading
Not comparable

Reasoning

Not comparable
Mercury 3
Not ranked
Qwen3.5 397B
74.1
Unranked · 2 rankable rows
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Mercury 3
Not ranked
Qwen3.5 397B
73.6
#29/55
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Mercury 3
Not ranked
Qwen3.5 397B
53.3
Estimated · #70/186
Basis
BenchAlign v5.8 lane · 1 vs 6 public rows
Reading
Not comparable

Multilingual

Not comparable
Mercury 3
Not ranked
Qwen3.5 397B
93.8
#5/17
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Mercury 3
Not ranked
Qwen3.5 397B
79.9
#59/148
Basis
Provisional lane · 1 vs 1 weighted rows
Reading
Not comparable

Math

Not comparable
Mercury 3
Not ranked
Qwen3.5 397B
81.7
Unranked · 5 rankable rows
Basis
Provisional lane · 0 vs 2 weighted rows
Reading
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.

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

Mercury 3
$0.00028
Fits in one request
Qwen3.5 397B
$0.0024
Fits in one request

Mercury 3 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Mercury 3
$0.00605
Fits in one request
Qwen3.5 397B
$0.0408
Fits in one request

Mercury 3 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Mercury 3
$0.0075
Fits in one request
Qwen3.5 397B
$0.168
Does not fit in one request
Cached input priced at the published list-input rate

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.

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.

Documented inputs

Mercury 3

Not sourced

Qwen3.5 397B

Not sourced

Documented outputs

Mercury 3

Not sourced

Qwen3.5 397B

Not sourced

Provider availability

Mercury 3

Not sourced

Qwen3.5 397B

Not sourced

Reasoning profile

Mercury 3

Reasoning

Qwen3.5 397B

Non-Reasoning

Weight access

Mercury 3

Proprietary

Qwen3.5 397B

Open Weight

License

Mercury 3

Proprietary

Qwen3.5 397B

Open Weight

Release date

Mercury 3

2026-10-19

Qwen3.5 397B

2026-02-16

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
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
Repository review: $0.00605 vs $0.0408. Cache-heavy agent loop: $0.0075 vs $0.168.
Context tradeoff
Mercury 3 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Mercury 3 or Qwen3.5 397B?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Mercury 3 or Qwen3.5 397B?

Mercury 3 and Qwen3.5 397B are not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Mercury 3 or Qwen3.5 397B?

Mercury 3 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Mercury 3 or Qwen3.5 397B?

For the stated presets, chat costs $0.00028 on Mercury 3 and $0.0024 on Qwen3.5 397B; repository review costs $0.00605 and $0.0408; the cache-heavy agent loop costs $0.0075 and $0.168. 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.

Which has the larger context window, Mercury 3 or Qwen3.5 397B?

Mercury 3 has the larger documented context window: 1M, compared with 128K.

Benchmark evidence

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

Browse raw public benchmark evidence68 rows

Agentic

  • τ³-bench results

    Mercury 330.2%
    Source
    Qwen3.5 397B68.4%
    Source

    Qwen3.5 397B leads this result

  • BrowseComp+

    Mercury 355.18%
    Source
    Qwen3.5 397B—

    Not directly comparable

  • DeepSearchQA

    Mercury 371.3%
    Source
    Qwen3.5 397B—

    Not directly comparable

  • Terminal-Bench 2.0

    Mercury 3—
    Qwen3.5 397B52.5%
    Source

    Not directly comparable

  • BrowseComp

    Mercury 3—
    Qwen3.5 397B69%
    Source

    Not directly comparable

  • OSWorld-Verified

    Mercury 3—
    Qwen3.5 397B62.2%
    Source

    Not directly comparable

  • Claw-Eval

    Mercury 3—
    Qwen3.5 397B56.8%
    Source

    Not directly comparable

  • QwenClawBench

    Mercury 3—
    Qwen3.5 397B51.8%
    Source

    Not directly comparable

  • VITA-Bench

    Mercury 3—
    Qwen3.5 397B43.7%
    Source

    Not directly comparable

  • DeepPlanning

    Mercury 3—
    Qwen3.5 397B37.6%
    Source

    Not directly comparable

  • Toolathlon

    Mercury 3—
    Qwen3.5 397B36.3%
    Source

    Not directly comparable

  • MCP Atlas

    Mercury 3—
    Qwen3.5 397B46.1%
    Source

    Not directly comparable

  • MCP-Tasks

    Mercury 3—
    Qwen3.5 397B74.2%
    Source

    Not directly comparable

  • WideResearch

    Mercury 3—
    Qwen3.5 397B74.0%
    Source

    Not directly comparable

  • Gert Labs

    Mercury 3—
    Qwen3.5 397B46.76%
    Source

    Not directly comparable

  • ResearchClawBench

    Mercury 3—
    Qwen3.5 397B14.2%
    Source

    Not directly comparable

Coding

  • DeepSWE

    Mercury 346.3%
    Source
    Qwen3.5 397B—

    Not directly comparable

  • SWE-bench Verified

    Mercury 3—
    Qwen3.5 397B76.2%
    Source

    Not directly comparable

  • LiveCodeBench v6

    Mercury 3—
    Qwen3.5 397B83.6%
    Source

    Not directly comparable

  • SWE-bench Pro

    Mercury 3—
    Qwen3.5 397B50.9%
    Source

    Not directly comparable

  • SWE Multilingual

    Mercury 3—
    Qwen3.5 397B69.3%
    Source

    Not directly comparable

  • NL2Repo

    Mercury 3—
    Qwen3.5 397B32.2%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Mercury 3—
    Qwen3.5 397B52.5%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    Mercury 375.5%
    Source
    Qwen3.5 397B—

    Not directly comparable

  • LongBench v2

    Mercury 3—
    Qwen3.5 397B63.2%
    Source

    Not directly comparable

  • AI-Needle

    Mercury 3—
    Qwen3.5 397B68.7%
    Source

    Not directly comparable

Multimodal

  • MMMU

    Mercury 3—
    Qwen3.5 397B85.0%
    Source

    Not directly comparable

  • MMMU-Pro

    Mercury 3—
    Qwen3.5 397B79%
    Source

    Not directly comparable

  • RealWorldQA

    Mercury 3—
    Qwen3.5 397B83.9%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Mercury 3—
    Qwen3.5 397B90.8%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Mercury 3—
    Qwen3.5 397B87.5%
    Source

    Not directly comparable

  • Video-MME (w/o subtitle)

    Mercury 3—
    Qwen3.5 397B83.7%
    Source

    Not directly comparable

  • MathVision

    Mercury 3—
    Qwen3.5 397B88.6%
    Source

    Not directly comparable

  • We-Math

    Mercury 3—
    Qwen3.5 397B87.9%
    Source

    Not directly comparable

  • DynaMath

    Mercury 3—
    Qwen3.5 397B86.3%
    Source

    Not directly comparable

  • SimpleVQA

    Mercury 3—
    Qwen3.5 397B67.1%
    Source

    Not directly comparable

  • CharXiv

    Mercury 3—
    Qwen3.5 397B80.8%
    Source

    Not directly comparable

  • MMLongBench-Doc

    Mercury 3—
    Qwen3.5 397B61.5%
    Source

    Not directly comparable

  • CC-OCR

    Mercury 3—
    Qwen3.5 397B82.0%
    Source

    Not directly comparable

  • AI2D_TEST

    Mercury 3—
    Qwen3.5 397B93.9%
    Source

    Not directly comparable

  • CountBench

    Mercury 3—
    Qwen3.5 397B97.2%
    Source

    Not directly comparable

  • RefCOCO (avg)

    Mercury 3—
    Qwen3.5 397B92.3%
    Source

    Not directly comparable

  • ODINW13

    Mercury 3—
    Qwen3.5 397B47.0%
    Source

    Not directly comparable

  • ERQA

    Mercury 3—
    Qwen3.5 397B67.5%
    Source

    Not directly comparable

  • VideoMMMU

    Mercury 3—
    Qwen3.5 397B84.7%
    Source

    Not directly comparable

  • MLVU (M-Avg)

    Mercury 3—
    Qwen3.5 397B86.7%
    Source

    Not directly comparable

  • ScreenSpot Pro

    Mercury 3—
    Qwen3.5 397B65.6%
    Source

    Not directly comparable

  • V*

    Mercury 3—
    Qwen3.5 397B95.8%
    Source

    Not directly comparable

Knowledge

  • GPQA-D

    Mercury 389.2%
    Source
    Qwen3.5 397B—

    Not directly comparable

  • GPQA

    Mercury 3—
    Qwen3.5 397B88.4%
    Source

    Not directly comparable

  • SuperGPQA

    Mercury 3—
    Qwen3.5 397B70.4%
    Source

    Not directly comparable

  • MMLU-Pro

    Mercury 3—
    Qwen3.5 397B87.8%
    Source

    Not directly comparable

  • MMLU-Redux

    Mercury 3—
    Qwen3.5 397B94.9%
    Source

    Not directly comparable

  • C-Eval

    Mercury 3—
    Qwen3.5 397B93%
    Source

    Not directly comparable

  • HLE

    Mercury 3—
    Qwen3.5 397B28.7%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    Mercury 3—
    Qwen3.5 397B84.7%
    Source

    Not directly comparable

  • NOVA-63

    Mercury 3—
    Qwen3.5 397B59.1%
    Source

    Not directly comparable

  • INCLUDE

    Mercury 3—
    Qwen3.5 397B85.6%
    Source

    Not directly comparable

  • PolyMath

    Mercury 3—
    Qwen3.5 397B73.3%
    Source

    Not directly comparable

  • MAXIFE

    Mercury 3—
    Qwen3.5 397B88.2%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Mercury 376.8%
    Source
    Qwen3.5 397B76.5%
    Source

    Mercury 3 leads this result

  • MultiChallenge (provider reports)

    Mercury 360.35%
    Source
    Qwen3.5 397B—

    Not directly comparable

  • IFEval

    Mercury 3—
    Qwen3.5 397B92.6%
    Source

    Not directly comparable

Math

  • AIME26

    Mercury 3—
    Qwen3.5 397B93.3%
    Source

    Not directly comparable

  • HMMT Feb 2025

    Mercury 3—
    Qwen3.5 397B94.8%
    Source

    Not directly comparable

  • HMMT Nov 2025

    Mercury 3—
    Qwen3.5 397B92.7%
    Source

    Not directly comparable

  • HMMT Feb 2026

    Mercury 3—
    Qwen3.5 397B87.9%
    Source

    Not directly comparable

  • MMAnswerBench

    Mercury 3—
    Qwen3.5 397B80.9%
    Source

    Not directly comparable

68 public results · 2 shared

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Last updated October 19, 2026