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BenchLM
Model A
Claude Haiku 4.5

Anthropic

56.3/100

Estimated · Public rank #84

90% interval 44.8–67.8

Claude Haiku 4.5 vs Qwen3.5-35B-A3B

Updated August 13, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
Qwen3.5-35B-A3B

Alibaba

56.0/100

Supported · Public rank #86

90% interval 44.6–67.4

Decision reading

Claude Haiku 4.5 has the higher public score estimate, 56.28 versus 55.97, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

1 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.

  • Long documents

    Prompts that approach the documented context limit

    Qwen3.5-35B-A3B

    Qwen3.5-35B-A3B has the larger documented context window.

    Confidence: documented

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

  • 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. Claude Haiku 4.5 does not fit this workload in one request. Qwen3.5-35B-A3B has no comparable published API token rate.

    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
1
Claude Haiku 4.5 only
5
Qwen3.5-35B-A3B only
15
Like-for-like categories
0 / 8

1 category uses 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
Claude Haiku 4.5
73.3
Qwen3.5-35B-A3B
60.6
Weighted basis
1 vs 2 rows
Reading
Directional only

Agentic

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.5-35B-A3B
51.0
Weighted basis
0 vs 3 rows
Reading
Not comparable

Reasoning

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.5-35B-A3B
59.0
Weighted basis
0 vs 1 rows
Reading
Not comparable

Knowledge

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.5-35B-A3B
81.6
Weighted basis
0 vs 3 rows
Reading
Not comparable

Math

Not comparable
Claude Haiku 4.5
4.9
Qwen3.5-35B-A3B
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.5-35B-A3B
81.0
Weighted basis
0 vs 1 rows
Reading
Not comparable

Multimodal

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.5-35B-A3B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.5-35B-A3B
91.9
Weighted basis
0 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

Claude Haiku 4.5
$0.0035
Fits in one request
Qwen3.5-35B-A3B
Self-hosted; infrastructure cost varies
Fits in one request

Qwen3.5-35B-A3B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Haiku 4.5
$0.065
Fits in one request
Qwen3.5-35B-A3B
Self-hosted; infrastructure cost varies
Fits in one request

Qwen3.5-35B-A3B has no comparable published API token rate.

Cache-heavy agent loop

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

Claude Haiku 4.5
$0.09
Does not fit in one request
Qwen3.5-35B-A3B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Claude Haiku 4.5 does not fit this workload in one request. Qwen3.5-35B-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.

Claude Haiku 4.5

200K

Claude API pricing

Qwen3.5-35B-A3B

262K

API model ID

Claude Haiku 4.5

claude-haiku-4-5-20251001

Claude API pricing

Qwen3.5-35B-A3B

Not sourced

Cached-input rate

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

Claude Haiku 4.5

$0.1 per 1M cached input tokens

Claude API pricing

Qwen3.5-35B-A3B

No comparable hosted API rate

Documented inputs

Claude Haiku 4.5

Not sourced

Qwen3.5-35B-A3B

Not sourced

Documented outputs

Claude Haiku 4.5

Not sourced

Qwen3.5-35B-A3B

Not sourced

Provider availability

Claude Haiku 4.5

Not sourced

Qwen3.5-35B-A3B

Not sourced

Reasoning profile

Claude Haiku 4.5

Non-Reasoning

Qwen3.5-35B-A3B

Reasoning

Weight access

Claude Haiku 4.5

Proprietary

Qwen3.5-35B-A3B

Open Weight

License

Claude Haiku 4.5

Proprietary

Qwen3.5-35B-A3B

Open Weight

Release date

Claude Haiku 4.5

2025-10-15

Qwen3.5-35B-A3B

2026-03-04

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
Claude Haiku 4.5 has the higher public score estimate, 56.28 versus 55.97, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Qwen3.5-35B-A3B has the larger documented window (262K).

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 evidence21 rows

Agentic

  • JobBench

    Claude Haiku 4.516.0%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B40.5%
    Source

    Not directly comparable

  • BrowseComp

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B61%
    Source

    Not directly comparable

  • OSWorld-Verified

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B54.5%
    Source

    Not directly comparable

  • Gert Labs

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B28.96%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Haiku 4.573.3%
    Source
    Qwen3.5-35B-A3B69.2%
    Source

    Claude Haiku 4.5 leads this result

  • VulcanBench v3

    Claude Haiku 4.578.3%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • EEBench

    Claude Haiku 4.53.5%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • SWE-Rebench

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B53.7%
    Source

    Not directly comparable

Reasoning

  • LongBench v2

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B59%
    Source

    Not directly comparable

Knowledge

  • MMLU-Pro

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B85.3%
    Source

    Not directly comparable

  • SuperGPQA

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B63.4%
    Source

    Not directly comparable

  • GPQA

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B84.2%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Claude Haiku 4.55.903%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Haiku 4.52.083%
    Source
    Qwen3.5-35B-A3B—

    Not directly comparable

Multilingual

  • MMLU-ProX

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B81%
    Source

    Not directly comparable

Multimodal

  • MMMU

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B81.4%
    Source

    Not directly comparable

  • MMVU

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B72.3%
    Source

    Not directly comparable

  • MathVision

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B83.9%
    Source

    Not directly comparable

  • V*

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B92.7%
    Source

    Not directly comparable

Instruction following

  • IFEval

    Claude Haiku 4.5—
    Qwen3.5-35B-A3B91.9%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude Haiku 4.5 or Qwen3.5-35B-A3B?

Claude Haiku 4.5 has the higher public score estimate, 56.28 versus 55.97, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Claude Haiku 4.5 or Qwen3.5-35B-A3B?

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, Claude Haiku 4.5 or Qwen3.5-35B-A3B?

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, Claude Haiku 4.5 or Qwen3.5-35B-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, Claude Haiku 4.5 or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B has the larger documented context window: 262K, compared with 200K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 13, 2026

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