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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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IBM logo
Model A
Granite 4.2 8B

IBM

46.88/100

Estimated · Public rank #162

90% interval 35.4–58.4

Granite 4.2 8B vs Qwen3.5 397B

Updated August 31, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Alibaba logo
Model B
Qwen3.5 397B

Alibaba

58.2/100

Estimated · Public rank #87

90% interval 46.7–69.7

Decision reading

Qwen3.5 397B has the higher public score estimate, 58.2 versus 46.88, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

7 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

    No shared weighted benchmark basis supports a winner.

    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

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Granite 4.2 8B does not fit this 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. Granite 4.2 8B 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
7
Granite 4.2 8B only
7
Qwen3.5 397B only
31
Like-for-like categories
0 / 8

2 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.

Coding

Directional only
Granite 4.2 8B
36.5
Qwen3.5 397B
66.5
Weighted basis
3 vs 2 rows
Reading
Directional only

Knowledge

Directional only
Granite 4.2 8B
72.2
Qwen3.5 397B
56.6
Weighted basis
2 vs 4 rows
Reading
Directional only

Agentic

Not comparable
Granite 4.2 8B
Not measured
Qwen3.5 397B
56.5
Weighted basis
0 vs 2 rows
Reading
Not comparable

Reasoning

Not comparable
Granite 4.2 8B
Not measured
Qwen3.5 397B
63.2
Weighted basis
0 vs 1 rows
Reading
Not comparable

Math

Not comparable
Granite 4.2 8B
Not measured
Qwen3.5 397B
90.6
Weighted basis
0 vs 2 rows
Reading
Not comparable

Multilingual

Not comparable
Granite 4.2 8B
Not measured
Qwen3.5 397B
84.7
Weighted basis
0 vs 1 rows
Reading
Not comparable

Multimodal

Not comparable
Granite 4.2 8B
Not measured
Qwen3.5 397B
79.6
Weighted basis
0 vs 2 rows
Reading
Not comparable

Instruction following

Not comparable
Granite 4.2 8B
79.3
Qwen3.5 397B
92.6
Weighted basis
1 vs 1 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

Granite 4.2 8B
Self-hosted; infrastructure cost varies
Fits in one request
Qwen3.5 397B
$0.0024
Fits in one request

Granite 4.2 8B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Granite 4.2 8B
Self-hosted; infrastructure cost varies
Fits in one request
Qwen3.5 397B
$0.0408
Fits in one request

Granite 4.2 8B has no comparable published API token rate.

Cache-heavy agent loop

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

Granite 4.2 8B
Self-hosted; infrastructure cost varies
Does not fit in one request
Cached-input rate unavailable
Qwen3.5 397B
$0.168
Does not fit in one request
Cached input priced at the published list-input rate

Granite 4.2 8B does not fit this 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. Granite 4.2 8B 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.

Cached-input rate

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

Granite 4.2 8B

No comparable hosted API rate

IBM Granite 4.2 8B model card

Qwen3.5 397B

Not published

Documented inputs

Granite 4.2 8B

Not sourced

Qwen3.5 397B

Not sourced

Documented outputs

Granite 4.2 8B

Not sourced

Qwen3.5 397B

Not sourced

Provider availability

Granite 4.2 8B

Not sourced

Qwen3.5 397B

Not sourced

Reasoning profile

Granite 4.2 8B

Reasoning

Qwen3.5 397B

Non-Reasoning

Weight access

Granite 4.2 8B

Open Weight

Qwen3.5 397B

Open Weight

License

Granite 4.2 8B

Open Weight

Qwen3.5 397B

Open Weight

Release date

Granite 4.2 8B

2026-08-25

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
Qwen3.5 397B has the higher public score estimate, 58.2 versus 46.88, 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 128K.

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 evidence45 rows

Agentic

  • Terminal-Bench 2.1

    Granite 4.2 8B20.6%
    Source
    Qwen3.5 397B

    Not directly comparable

  • τ³-bench results

    Granite 4.2 8B58.1%
    Source
    Qwen3.5 397B68.4%
    Source

    Qwen3.5 397B leads this result

  • BFCL v4

    Granite 4.2 8B52.4%
    Source
    Qwen3.5 397B

    Not directly comparable

  • Terminal-Bench 2.0

    Granite 4.2 8B
    Qwen3.5 397B52.5%
    Source

    Not directly comparable

  • BrowseComp

    Granite 4.2 8B
    Qwen3.5 397B62%
    Source

    Not directly comparable

  • Claw-Eval

    Granite 4.2 8B
    Qwen3.5 397B56.8%
    Source

    Not directly comparable

  • QwenClawBench

    Granite 4.2 8B
    Qwen3.5 397B51.8%
    Source

    Not directly comparable

  • VITA-Bench

    Granite 4.2 8B
    Qwen3.5 397B43.7%
    Source

    Not directly comparable

  • DeepPlanning

    Granite 4.2 8B
    Qwen3.5 397B37.6%
    Source

    Not directly comparable

  • Toolathlon

    Granite 4.2 8B
    Qwen3.5 397B36.3%
    Source

    Not directly comparable

  • MCP Atlas

    Granite 4.2 8B
    Qwen3.5 397B46.1%
    Source

    Not directly comparable

  • MCP-Tasks

    Granite 4.2 8B
    Qwen3.5 397B74.2%
    Source

    Not directly comparable

  • WideResearch

    Granite 4.2 8B
    Qwen3.5 397B74.0%
    Source

    Not directly comparable

  • Gert Labs

    Granite 4.2 8B
    Qwen3.5 397B46.76%
    Source

    Not directly comparable

  • ResearchClawBench

    Granite 4.2 8B
    Qwen3.5 397B14.2%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Granite 4.2 8B47.7%
    Source
    Qwen3.5 397B76.2%
    Source

    Qwen3.5 397B leads this result

  • SWE-bench Pro

    Granite 4.2 8B19.1%
    Source
    Qwen3.5 397B50.9%
    Source

    Qwen3.5 397B leads this result

  • SWE Multilingual

    Granite 4.2 8B30.8%
    Source
    Qwen3.5 397B

    Not directly comparable

  • Terminal-Bench 2.1

    Granite 4.2 8B20.6%
    Source
    Qwen3.5 397B

    Not directly comparable

  • LiveCodeBench v6

    Granite 4.2 8B73.2%
    Source
    Qwen3.5 397B83.6%
    Source

    Qwen3.5 397B leads this result

  • SciCode

    Granite 4.2 8B36.1%
    Source
    Qwen3.5 397B

    Not directly comparable

Reasoning

  • LongBench v2

    Granite 4.2 8B
    Qwen3.5 397B63.2%
    Source

    Not directly comparable

  • AI-Needle

    Granite 4.2 8B
    Qwen3.5 397B68.7%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Granite 4.2 8B64.1%
    Source
    Qwen3.5 397B88.4%
    Source

    Qwen3.5 397B leads this result

  • MMLU-Pro

    Granite 4.2 8B74.0%
    Source
    Qwen3.5 397B87.8%
    Source

    Qwen3.5 397B leads this result

  • SuperGPQA

    Granite 4.2 8B
    Qwen3.5 397B70.4%
    Source

    Not directly comparable

  • MMLU-Redux

    Granite 4.2 8B
    Qwen3.5 397B94.9%
    Source

    Not directly comparable

  • C-Eval

    Granite 4.2 8B
    Qwen3.5 397B93%
    Source

    Not directly comparable

  • HLE

    Granite 4.2 8B
    Qwen3.5 397B28.7%
    Source

    Not directly comparable

Math

  • AIME 2025

    Granite 4.2 8B86.7%
    Source
    Qwen3.5 397B

    Not directly comparable

  • HMMT Feb 2025

    Granite 4.2 8B78.3%
    Source
    Qwen3.5 397B94.8%
    Source

    Qwen3.5 397B leads this result

  • AIME26

    Granite 4.2 8B
    Qwen3.5 397B93.3%
    Source

    Not directly comparable

  • HMMT Nov 2025

    Granite 4.2 8B
    Qwen3.5 397B92.7%
    Source

    Not directly comparable

  • HMMT Feb 2026

    Granite 4.2 8B
    Qwen3.5 397B87.9%
    Source

    Not directly comparable

  • MMAnswerBench

    Granite 4.2 8B
    Qwen3.5 397B80.9%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    Granite 4.2 8B
    Qwen3.5 397B84.7%
    Source

    Not directly comparable

  • NOVA-63

    Granite 4.2 8B
    Qwen3.5 397B59.1%
    Source

    Not directly comparable

Multimodal

  • MMMU-Pro

    Granite 4.2 8B
    Qwen3.5 397B79%
    Source

    Not directly comparable

  • MathVision

    Granite 4.2 8B
    Qwen3.5 397B88.6%
    Source

    Not directly comparable

  • CharXiv

    Granite 4.2 8B
    Qwen3.5 397B80.8%
    Source

    Not directly comparable

  • VideoMMMU

    Granite 4.2 8B
    Qwen3.5 397B84.7%
    Source

    Not directly comparable

  • ScreenSpot Pro

    Granite 4.2 8B
    Qwen3.5 397B65.6%
    Source

    Not directly comparable

  • V*

    Granite 4.2 8B
    Qwen3.5 397B95.8%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Granite 4.2 8B79.3%
    Source
    Qwen3.5 397B

    Not directly comparable

  • IFEval

    Granite 4.2 8B
    Qwen3.5 397B92.6%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Granite 4.2 8B or Qwen3.5 397B?

Qwen3.5 397B has the higher public score estimate, 58.2 versus 46.88, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Granite 4.2 8B or Qwen3.5 397B?

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, Granite 4.2 8B or Qwen3.5 397B?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Granite 4.2 8B or Qwen3.5 397B?

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, Granite 4.2 8B or Qwen3.5 397B?

Both models list the same context window, 128K.

Related comparisons

Last updated August 31, 2026

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