Agentic
Like-for-like- Claude Haiku 4.5
- 27.0
- Supported · #143/151
- Qwen3.6-27B
- 33.9
- Supported · #133/151
- Basis
- BenchAlign lane · 2 vs 6 public rows
- Reading
- Qwen3.6-27B leads · intervals overlap
Claude Haiku 4.5 vs Qwen3.6-27B
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Haiku 4.5 and Qwen3.6-27B have the same public score on the current data.
1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
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.
Coding work
Code generation, repair, and software-engineering tasks
Qwen3.6-27B
Qwen3.6-27B leads on the public coding lane, 42.6 to 27.3, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Qwen3.6-27B
Qwen3.6-27B leads on the public agentic lane, 33.9 to 27, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Qwen3.6-27B
Qwen3.6-27B has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
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. Qwen3.6-27B 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.
9 Claude Haiku 4.5 only
1 Shared
37 Qwen3.6-27B only
- Shared results
- 1
- Claude Haiku 4.5 only
- 9
- Qwen3.6-27B only
- 37
- Like-for-like categories
- 2 / 8
1 category rests 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.
Coding
Like-for-like- Claude Haiku 4.5
- 27.3
- Supported · #173/183
- Qwen3.6-27B
- 42.6
- Supported · #128/183
- Basis
- BenchAlign lane · 4 vs 6 public rows
- Reading
- Qwen3.6-27B leads · intervals overlap
Knowledge
Directional only- Claude Haiku 4.5
- 44.6
- Estimated · #117/181
- Qwen3.6-27B
- 49.0
- Estimated · #95/181
- Basis
- BenchAlign lane · 2 vs 6 public rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Haiku 4.5
- Not ranked
- Qwen3.6-27B
- 73.7
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Haiku 4.5
- 28.9
- Unranked · 2 rankable rows
- Qwen3.6-27B
- 72.8
- Unranked · 5 rankable rows
- Basis
- Provisional lane · 2 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Haiku 4.5
- Not ranked
- Qwen3.6-27B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Claude Haiku 4.5
- Not ranked
- Qwen3.6-27B
- 51.5
- #35/48
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Haiku 4.5
- Not ranked
- Qwen3.6-27B
- 82.2
- #50/120
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Haiku 4.5 | Qwen3.6-27B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 27.0Supported · #143/151 | 33.9Supported · #133/151 | Like-for-likeBenchAlign lane · 2 vs 6 public rows | Qwen3.6-27B leads · intervals overlap |
| Coding | 27.3Supported · #173/183 | 42.6Supported · #128/183 | Like-for-likeBenchAlign lane · 4 vs 6 public rows | Qwen3.6-27B leads · intervals overlap |
| Knowledge | 44.6Estimated · #117/181 | 49.0Estimated · #95/181 | Directional onlyBenchAlign lane · 2 vs 6 public rows | Directional only |
| Reasoning | Not ranked | 73.7Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 28.9Unranked · 2 rankable rows | 72.8Unranked · 5 rankable rows | Not comparableProvisional lane · 2 vs 2 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | 51.5#35/48 | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Instruction following | Not ranked | 82.2#50/120 | Not comparableProvisional lane · 0 vs 0 weighted rows | 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.
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.
SWE-bench Verified
Coding
Claude Haiku 4.5: 73.3%Qwen3.6-27B: 77.2%Normalized gap 3.9Claude Haiku 4.5 source Qwen3.6-27B source
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
- Qwen3.6-27B
- Self-hosted; infrastructure cost varies
- Fits in one request
Qwen3.6-27B 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
- Qwen3.6-27B
- Self-hosted; infrastructure cost varies
- Fits in one request
Qwen3.6-27B 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
- Qwen3.6-27B
- 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. Qwen3.6-27B 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.
SpecificationClaude Haiku 4.5Qwen3.6-27B
Context window
Maximum documented context; output-token limits may be lower.
Claude Haiku 4.5
Qwen3.6-27B
262K
API model ID
Claude Haiku 4.5
claude-haiku-4-5-20251001
Claude API pricingQwen3.6-27B
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 pricingQwen3.6-27B
No comparable hosted API rate
Documented inputs
Claude Haiku 4.5
Not sourced
Qwen3.6-27B
Not sourced
Documented outputs
Claude Haiku 4.5
Not sourced
Qwen3.6-27B
Not sourced
Provider availability
Claude Haiku 4.5
Not sourced
Qwen3.6-27B
Not sourced
Reasoning profile
Claude Haiku 4.5
Non-Reasoning
Qwen3.6-27B
Reasoning
Weight access
Claude Haiku 4.5
Proprietary
Qwen3.6-27B
Open Weight
License
Claude Haiku 4.5
Proprietary
Qwen3.6-27B
Open Weight
Release date
Claude Haiku 4.5
2025-10-15
Qwen3.6-27B
2026-04-21
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 and Qwen3.6-27B have the same public score on the current data.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Qwen3.6-27B has the larger documented window (262K).
Run the same representative tasks against both endpoints before changing production traffic.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Claude Haiku 4.5
API / mo$4,500
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Qwen3.6-27B
API / mo$0
Self-host / mo$429
Break-even—
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence47 rows
Agentic
JobBench
Claude Haiku 4.516.0%SourceQwen3.6-27B—Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Haiku 4.543.8%SourceQwen3.6-27B—Not directly comparable
Terminal-Bench 2.0
Claude Haiku 4.5—Qwen3.6-27B59.3%SourceNot directly comparable
Claw-Eval
Claude Haiku 4.5—Qwen3.6-27B72.4%SourceNot directly comparable
QwenClawBench
Claude Haiku 4.5—Qwen3.6-27B53.4%SourceNot directly comparable
QwenWebBench
Claude Haiku 4.5—Qwen3.6-27B1487SourceNot directly comparable
AndroidWorld
Claude Haiku 4.5—Qwen3.6-27B70.3%SourceNot directly comparable
Gert Labs
Claude Haiku 4.5—Qwen3.6-27B54.84%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Haiku 4.573.3%SourceQwen3.6-27B77.2%SourceQwen3.6-27B leads this result
VulcanBench v3
Claude Haiku 4.576.2%SourceQwen3.6-27B—Not directly comparable
LiveCodeBench (Vals)
Claude Haiku 4.541.2%SourceQwen3.6-27B—Not directly comparable
SWE-bench (Vals)
Claude Haiku 4.566.6%SourceQwen3.6-27B—Not directly comparable
SWE Multilingual
Claude Haiku 4.5—Qwen3.6-27B71.3%SourceNot directly comparable
SWE-bench Pro
Claude Haiku 4.5—Qwen3.6-27B53.5%SourceNot directly comparable
Terminal-Bench 2.0
Claude Haiku 4.5—Qwen3.6-27B59.3%SourceNot directly comparable
LiveCodeBench
Claude Haiku 4.5—Qwen3.6-27B83.9%SourceNot directly comparable
NL2Repo
Claude Haiku 4.5—Qwen3.6-27B36.2%SourceNot directly comparable
Knowledge
GPQA Diamond (Vals)
Claude Haiku 4.572.2%SourceQwen3.6-27B—Not directly comparable
MMLU-Pro (Vals)
Claude Haiku 4.578.7%SourceQwen3.6-27B—Not directly comparable
MMLU-Pro
Claude Haiku 4.5—Qwen3.6-27B86.2%SourceNot directly comparable
MMLU-Redux
Claude Haiku 4.5—Qwen3.6-27B93.5%SourceNot directly comparable
SuperGPQA
Claude Haiku 4.5—Qwen3.6-27B66%SourceNot directly comparable
C-Eval
Claude Haiku 4.5—Qwen3.6-27B91.4%SourceNot directly comparable
GPQA
Claude Haiku 4.5—Qwen3.6-27B87.8%SourceNot directly comparable
HLE
Claude Haiku 4.5—Qwen3.6-27B24%SourceNot directly comparable
Math
FrontierMath v2 (Tiers 1-3)
Claude Haiku 4.55.903%SourceQwen3.6-27B—Not directly comparable
FrontierMath v2 (Tier 4)
Claude Haiku 4.52.083%SourceQwen3.6-27B—Not directly comparable
HMMT Feb 2025
Claude Haiku 4.5—Qwen3.6-27B93.8%SourceNot directly comparable
HMMT Nov 2025
Claude Haiku 4.5—Qwen3.6-27B90.7%SourceNot directly comparable
HMMT Feb 2026
Claude Haiku 4.5—Qwen3.6-27B84.3%SourceNot directly comparable
MMAnswerBench
Claude Haiku 4.5—Qwen3.6-27B80.8%SourceNot directly comparable
AIME26
Claude Haiku 4.5—Qwen3.6-27B94.1%SourceNot directly comparable
Multimodal
MMMU
Claude Haiku 4.5—Qwen3.6-27B82.9%SourceNot directly comparable
MMMU-Pro
Claude Haiku 4.5—Qwen3.6-27B75.8%SourceNot directly comparable
RealWorldQA
Claude Haiku 4.5—Qwen3.6-27B84.1%SourceNot directly comparable
DynaMath
Claude Haiku 4.5—Qwen3.6-27B85.6%SourceNot directly comparable
MStar
Claude Haiku 4.5—Qwen3.6-27B81.4%SourceNot directly comparable
SimpleVQA
Claude Haiku 4.5—Qwen3.6-27B56.1%SourceNot directly comparable
CharXiv
Claude Haiku 4.5—Qwen3.6-27B78.4%SourceNot directly comparable
CC-OCR
Claude Haiku 4.5—Qwen3.6-27B81.2%SourceNot directly comparable
CountBench
Claude Haiku 4.5—Qwen3.6-27B97.8%SourceNot directly comparable
RefCOCO (avg)
Claude Haiku 4.5—Qwen3.6-27B92.5%SourceNot directly comparable
ERQA
Claude Haiku 4.5—Qwen3.6-27B62.5%SourceNot directly comparable
Video-MME (with subtitle)
Claude Haiku 4.5—Qwen3.6-27B87.7%SourceNot directly comparable
VideoMMMU
Claude Haiku 4.5—Qwen3.6-27B84.4%SourceNot directly comparable
MLVU (M-Avg)
Claude Haiku 4.5—Qwen3.6-27B86.6%SourceNot directly comparable
V*
Claude Haiku 4.5—Qwen3.6-27B94.7%SourceNot directly comparable
Frequently asked questions
Which is better, Claude Haiku 4.5 or Qwen3.6-27B?
Claude Haiku 4.5 and Qwen3.6-27B have the same public score on the current data. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Claude Haiku 4.5 or Qwen3.6-27B?
Qwen3.6-27B leads the public coding lane, 42.6 to 27.3, with Supported evidence for both models, although the 90% intervals overlap.
Which is better for agentic tasks, Claude Haiku 4.5 or Qwen3.6-27B?
Qwen3.6-27B leads the public agentic tasks lane, 33.9 to 27, with Supported evidence for both models, although the 90% intervals overlap.
Which costs less, Claude Haiku 4.5 or Qwen3.6-27B?
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 Qwen3.6-27B?
Qwen3.6-27B has the larger documented context window: 262K, compared with 200K.
Related comparisons
Last updated September 4, 2026
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