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BenchLM
Model A
Claude Haiku 4.5

Anthropic

57.1/100

Estimated · Public rank #86

90% interval 45.5–68.6

Claude Haiku 4.5 vs Qwen3.6 Plus

Updated August 18, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B
Qwen3.6 Plus

Alibaba

64.8/100

Supported · Public rank #36

90% interval 55.7–73.9

Decision reading

Qwen3.6 Plus has the higher public score estimate, 64.79 versus 57.06, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

4 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

    Qwen3.6 Plus

    Qwen3.6 Plus 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. Qwen3.6 Plus 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
4
Claude Haiku 4.5 only
2
Qwen3.6 Plus only
40
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
Claude Haiku 4.5
73.3
Qwen3.6 Plus
70.3
Weighted basis
1 vs 2 rows
Reading
Directional only

Math

Directional only
Claude Haiku 4.5
4.9
Qwen3.6 Plus
60.5
Weighted basis
2 vs 4 rows
Reading
Directional only

Agentic

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.6 Plus
61.6
Weighted basis
0 vs 1 rows
Reading
Not comparable

Reasoning

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.6 Plus
62.0
Weighted basis
0 vs 1 rows
Reading
Not comparable

Knowledge

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.6 Plus
57.1
Weighted basis
0 vs 4 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.6 Plus
84.7
Weighted basis
0 vs 1 rows
Reading
Not comparable

Multimodal

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.6 Plus
79.8
Weighted basis
0 vs 2 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Haiku 4.5
Not measured
Qwen3.6 Plus
82.3
Weighted basis
0 vs 2 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
Qwen3.6 Plus
API rate not published
Fits in one request

Qwen3.6 Plus 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
Qwen3.6 Plus
API rate not published
Fits in one request

Qwen3.6 Plus 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
Qwen3.6 Plus
API rate not published
Fits in one request
Cached-input rate unavailable

Claude Haiku 4.5 does not fit this workload in one request. Qwen3.6 Plus 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

Qwen3.6 Plus

1M

API model ID

Claude Haiku 4.5

claude-haiku-4-5-20251001

Claude API pricing

Qwen3.6 Plus

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

Qwen3.6 Plus

No comparable hosted API rate

Documented inputs

Claude Haiku 4.5

Not sourced

Qwen3.6 Plus

Not sourced

Documented outputs

Claude Haiku 4.5

Not sourced

Qwen3.6 Plus

Not sourced

Provider availability

Claude Haiku 4.5

Not sourced

Qwen3.6 Plus

Not sourced

Reasoning profile

Claude Haiku 4.5

Non-Reasoning

Qwen3.6 Plus

Reasoning

Weight access

Claude Haiku 4.5

Proprietary

Qwen3.6 Plus

Proprietary

License

Claude Haiku 4.5

Proprietary

Qwen3.6 Plus

Proprietary

Release date

Claude Haiku 4.5

2025-10-15

Qwen3.6 Plus

2026-04-02

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
Qwen3.6 Plus has the higher public score estimate, 64.79 versus 57.06, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Qwen3.6 Plus has the larger documented window (1M).

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 evidence46 rows

Agentic

  • JobBench

    Claude Haiku 4.516.0%
    Source
    Qwen3.6 Plus—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Haiku 4.5—
    Qwen3.6 Plus61.6%
    Source

    Not directly comparable

  • Claw-Eval

    Claude Haiku 4.5—
    Qwen3.6 Plus58.8%
    Source

    Not directly comparable

  • QwenClawBench

    Claude Haiku 4.5—
    Qwen3.6 Plus57.2%
    Source

    Not directly comparable

  • τ³-bench results

    Claude Haiku 4.5—
    Qwen3.6 Plus70.7%
    Source

    Not directly comparable

  • VITA-Bench

    Claude Haiku 4.5—
    Qwen3.6 Plus44.3%
    Source

    Not directly comparable

  • DeepPlanning

    Claude Haiku 4.5—
    Qwen3.6 Plus41.5%
    Source

    Not directly comparable

  • Toolathlon

    Claude Haiku 4.5—
    Qwen3.6 Plus39.8%
    Source

    Not directly comparable

  • MCP Atlas

    Claude Haiku 4.5—
    Qwen3.6 Plus48.2%
    Source

    Not directly comparable

  • MCP-Tasks

    Claude Haiku 4.5—
    Qwen3.6 Plus74.1%
    Source

    Not directly comparable

  • WideResearch

    Claude Haiku 4.5—
    Qwen3.6 Plus74.3%
    Source

    Not directly comparable

  • Gert Labs

    Claude Haiku 4.5—
    Qwen3.6 Plus50.60%
    Source

    Not directly comparable

  • ResearchClawBench

    Claude Haiku 4.5—
    Qwen3.6 Plus18.0%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Haiku 4.573.3%
    Source
    Qwen3.6 Plus78.8%
    Source

    Qwen3.6 Plus leads this result

  • VulcanBench v3

    Claude Haiku 4.578.3%
    Source
    Qwen3.6 Plus—

    Not directly comparable

  • EEBench

    Shared source
    Claude Haiku 4.53.5%
    Qwen3.6 Plus12.7%

    Qwen3.6 Plus leads this result

  • SWE-bench Pro

    Claude Haiku 4.5—
    Qwen3.6 Plus56.6%
    Source

    Not directly comparable

  • SWE Multilingual

    Claude Haiku 4.5—
    Qwen3.6 Plus73.8%
    Source

    Not directly comparable

  • LiveCodeBench v6

    Claude Haiku 4.5—
    Qwen3.6 Plus87.1%
    Source

    Not directly comparable

  • Vibe Code Bench

    Claude Haiku 4.5—
    Qwen3.6 Plus25.56%
    Source

    Not directly comparable

Reasoning

  • AI-Needle

    Claude Haiku 4.5—
    Qwen3.6 Plus68.3%
    Source

    Not directly comparable

  • LongBench v2

    Claude Haiku 4.5—
    Qwen3.6 Plus62%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Claude Haiku 4.5—
    Qwen3.6 Plus90.4%
    Source

    Not directly comparable

  • SuperGPQA

    Claude Haiku 4.5—
    Qwen3.6 Plus71.6%
    Source

    Not directly comparable

  • MMLU-Pro

    Claude Haiku 4.5—
    Qwen3.6 Plus88.5%
    Source

    Not directly comparable

  • MMLU-Redux

    Claude Haiku 4.5—
    Qwen3.6 Plus94.5%
    Source

    Not directly comparable

  • C-Eval

    Claude Haiku 4.5—
    Qwen3.6 Plus93.3%
    Source

    Not directly comparable

  • HLE

    Claude Haiku 4.5—
    Qwen3.6 Plus28.8%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    Claude Haiku 4.55.903%
    Qwen3.6 Plus26.207%

    Qwen3.6 Plus leads this result

  • FrontierMath v2 (Tier 4)

    Shared source
    Claude Haiku 4.52.083%
    Qwen3.6 Plus8.333%

    Qwen3.6 Plus leads this result

  • AIME26

    Claude Haiku 4.5—
    Qwen3.6 Plus95.3%
    Source

    Not directly comparable

  • HMMT Feb 2025

    Claude Haiku 4.5—
    Qwen3.6 Plus96.7%
    Source

    Not directly comparable

  • HMMT Nov 2025

    Claude Haiku 4.5—
    Qwen3.6 Plus94.6%
    Source

    Not directly comparable

  • HMMT Feb 2026

    Claude Haiku 4.5—
    Qwen3.6 Plus87.8%
    Source

    Not directly comparable

  • MMAnswerBench

    Claude Haiku 4.5—
    Qwen3.6 Plus83.8%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    Claude Haiku 4.5—
    Qwen3.6 Plus84.7%
    Source

    Not directly comparable

  • NOVA-63

    Claude Haiku 4.5—
    Qwen3.6 Plus57.9%
    Source

    Not directly comparable

Multimodal

  • MMMU

    Claude Haiku 4.5—
    Qwen3.6 Plus86.0%
    Source

    Not directly comparable

  • MMMU-Pro

    Claude Haiku 4.5—
    Qwen3.6 Plus78.8%
    Source

    Not directly comparable

  • MathVision

    Claude Haiku 4.5—
    Qwen3.6 Plus88.0%
    Source

    Not directly comparable

  • VideoMMMU

    Claude Haiku 4.5—
    Qwen3.6 Plus84.0%
    Source

    Not directly comparable

  • ScreenSpot Pro

    Claude Haiku 4.5—
    Qwen3.6 Plus68.2%
    Source

    Not directly comparable

  • CharXiv

    Claude Haiku 4.5—
    Qwen3.6 Plus81.5%
    Source

    Not directly comparable

  • V*

    Claude Haiku 4.5—
    Qwen3.6 Plus96.9%
    Source

    Not directly comparable

Instruction following

  • IFEval

    Claude Haiku 4.5—
    Qwen3.6 Plus94.3%
    Source

    Not directly comparable

  • IFBench

    Claude Haiku 4.5—
    Qwen3.6 Plus75.8%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude Haiku 4.5 or Qwen3.6 Plus?

Qwen3.6 Plus has the higher public score estimate, 64.79 versus 57.06, 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 Qwen3.6 Plus?

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 Qwen3.6 Plus?

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 Qwen3.6 Plus?

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 Qwen3.6 Plus?

Qwen3.6 Plus has the larger documented context window: 1M, compared with 200K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 18, 2026

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