Claude Haiku 5.5 vs Qwen3.8 Max

Updated October 7, 2026. Rank says Qwen3.8 Max is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Qwen3.8 Max has the higher public point estimate, 70.52 versus 66.32. Their conditional score ranges overlap. These ranges do not establish rank confidence. 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

Claude Haiku 5.5

Anthropic

66.32/100

Estimated · Public rank #28

Conditional range 52.0–80.7

Model B

Qwen3.8 Max

Alibaba

70.52/100

Supported · Public rank #16

90% interval 66.4–74.7

Shared results: 2
Claude Haiku 5.5 only: 3
Qwen3.8 Max only: 58
Like-for-like categories: 2 / 8

Estimated: Claude Haiku 5.5 · Supported: Qwen3.8 Max. 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.

Coding work
Code generation, repair, and software-engineering tasks
Claude Haiku 5.5
Claude Haiku 5.5 has the higher public coding point estimate, 60.9 to 54.5, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Qwen3.8 Max
Qwen3.8 Max has the higher public agentic point estimate, 65.5 to 62.1, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Confidence: limited

Show secondary and unsupported calls

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
A complete comparable API-rate estimate is not available for both models.
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

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.

Pick the job you would use them for

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

60.9Claude Haiku 5.554.5Qwen3.8 Max

Like-for-like · BenchAlign v5.8

Claude Haiku 5.5 has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

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

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

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.

HLE w/o toolsKnowledge
Normalized gap 2.3
Claude Haiku 5.5:45.9%
Qwen3.8 Max:43.6%
Claude Haiku 5.5 source Qwen3.8 Max source

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

Like-for-like

Claude Haiku 5.5: 62.1; Supported · #18/122
Qwen3.8 Max: 65.5; Supported · #14/122
Basis: BenchAlign v5.8 lane · 2 vs 15 public rows
Reading: Qwen3.8 Max leads · intervals overlap

Coding

Like-for-like

Claude Haiku 5.5: 60.9; Supported · #20/146
Qwen3.8 Max: 54.5; Supported · #33/146
Basis: BenchAlign v5.8 lane · 1 vs 12 public rows
Reading: Claude Haiku 5.5 leads · intervals overlap

Reasoning

Not comparable

Claude Haiku 5.5: 79.2; Unranked · 2 rankable rows
Qwen3.8 Max: 87.7; Unranked · 2 rankable rows
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Claude Haiku 5.5: Not ranked
Qwen3.8 Max: 88.4; #5/49
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Knowledge

Not comparable

Claude Haiku 5.5: Not ranked
Qwen3.8 Max: 65.7; Supported · #24/174
Basis: BenchAlign v5.8 lane · 1 vs 6 public rows
Reading: Not comparable

Multilingual

Not comparable

Claude Haiku 5.5: Not ranked
Qwen3.8 Max: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Claude Haiku 5.5: Not ranked
Qwen3.8 Max: 89.8; #16/125
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Claude Haiku 5.5: Not ranked
Qwen3.8 Max: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Claude Haiku 5.5 and Qwen3.8 Max
Category	Claude Haiku 5.5	Qwen3.8 Max	Basis	Reading
Agentic	62.1Supported · #18/122	65.5Supported · #14/122	Like-for-likeBenchAlign v5.8 lane · 2 vs 15 public rows	Qwen3.8 Max leads · intervals overlap
Coding	60.9Supported · #20/146	54.5Supported · #33/146	Like-for-likeBenchAlign v5.8 lane · 1 vs 12 public rows	Claude Haiku 5.5 leads · intervals overlap
Reasoning	79.2Unranked · 2 rankable rows	87.7Unranked · 2 rankable rows	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable
Multimodal	Not ranked	88.4#5/49	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable
Knowledge	Not ranked	65.7Supported · #24/174	Not comparableBenchAlign v5.8 lane · 1 vs 6 public rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	Not ranked	89.8#16/125	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	Not ranked	Not ranked	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 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.

Supported evidence per lane · 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

Claude Haiku 5.5: $0.00035; Fits in one request
Qwen3.8 Max: API rate not published; Fits in one request

Qwen3.8 Max has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Haiku 5.5: $0.0065; Fits in one request
Qwen3.8 Max: API rate not published; Fits in one request

Qwen3.8 Max has no comparable published API token rate.

Cache-heavy agent loop

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

Claude Haiku 5.5: $0.009; Fits in one request
Qwen3.8 Max: API rate not published; Fits in one request; Cached-input rate unavailable

Qwen3.8 Max has no comparable published API token 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.

SpecificationClaude Haiku 5.5Qwen3.8 Max

Context window

Maximum documented context; output-token limits may be lower.

Claude Haiku 5.5

Anthropic Claude Haiku 5.5 model documentation

Qwen3.8 Max

Alibaba Cloud Model Studio pricing

API model ID

Claude Haiku 5.5

claude-haiku-5-5

Anthropic Claude Haiku 5.5 model documentation

Qwen3.8 Max

qwen3.8-max

Alibaba Cloud Model Studio pricing

Cached-input rate

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

Claude Haiku 5.5

$0.01 per 1M cached input tokens

Claude API pricing

Qwen3.8 Max

No comparable hosted API rate

Alibaba Cloud Model Studio pricing

Documented inputs

Claude Haiku 5.5

text, image

Anthropic Claude Haiku 5.5 model documentation

Qwen3.8 Max

Not sourced

Documented outputs

Claude Haiku 5.5

text

Anthropic Claude Haiku 5.5 model documentation

Qwen3.8 Max

Not sourced

Provider availability

Claude Haiku 5.5

Generally Available · Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry, Claude Platform on AWS

Anthropic Claude Haiku 5.5 model documentation

Qwen3.8 Max

Not sourced

Reasoning profile

Claude Haiku 5.5

Reasoning

Qwen3.8 Max

Reasoning

Weight access

Claude Haiku 5.5

Proprietary

Qwen3.8 Max

Open Weight

License

Claude Haiku 5.5

Proprietary

Qwen3.8 Max

Open Weight

Release date

Claude Haiku 5.5

2026-10-07

Qwen3.8 Max

2026-08-03

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: Qwen3.8 Max has the higher public point estimate, 70.52 versus 66.32. Their conditional score ranges overlap. These ranges do not establish rank confidence.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Both models list 1M.

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Haiku 5.5 or Qwen3.8 Max?

Qwen3.8 Max has the higher public point estimate, 70.52 versus 66.32. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Claude Haiku 5.5 or Qwen3.8 Max?

Claude Haiku 5.5 has the higher public coding point estimate, 60.9 to 54.5, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, Claude Haiku 5.5 or Qwen3.8 Max?

Qwen3.8 Max has the higher public agentic tasks point estimate, 65.5 to 62.1, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which costs less, Claude Haiku 5.5 or Qwen3.8 Max?

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 5.5 or Qwen3.8 Max?

Both models list the same context window, 1M.

Benchmark evidence

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

Browse raw public benchmark evidence63 rows

Agentic

Terminal-Bench 4.0
Claude Haiku 5.539.20%
Source
Qwen3.8 Max—
Not directly comparable
HLE w/ tools
Claude Haiku 5.557.4%
Source
Qwen3.8 Max56.2%
Source
Claude Haiku 5.5 leads this result
Terminal-Bench 2.1
Claude Haiku 5.5—
Qwen3.8 Max86.6%
Source
Not directly comparable
CoWorkBench
Claude Haiku 5.5—
Qwen3.8 Max74.8%
Source
Not directly comparable
JobBench
Claude Haiku 5.5—
Qwen3.8 Max53.4%
Source
Not directly comparable
skillsBench
Claude Haiku 5.5—
Qwen3.8 Max70.2%
Source
Not directly comparable
Agents' Last Exam
Claude Haiku 5.5—
Qwen3.8 Max52.4%
Source
Not directly comparable
AutomationBench
Claude Haiku 5.5—
Qwen3.8 Max27.3%
Source
Not directly comparable
Toolathlon-Verified
Claude Haiku 5.5—
Qwen3.8 Max72.5%
Source
Not directly comparable
WideResearch
Claude Haiku 5.5—
Qwen3.8 Max81.9%
Source
Not directly comparable
OSWorld-Verified
Claude Haiku 5.5—
Qwen3.8 Max86.1%
Source
Not directly comparable
OSWorld 2.0
Claude Haiku 5.5—
Qwen3.8 Max19.4%
Source
Not directly comparable
WebArena-Verified
Claude Haiku 5.5—
Qwen3.8 Max66.8%
Source
Not directly comparable
AndroidWorld
Claude Haiku 5.5—
Qwen3.8 Max85.3%
Source
Not directly comparable
MobileWorld
Claude Haiku 5.5—
Qwen3.8 Max77.8%
Source
Not directly comparable
Terminal-Bench 2.1 (Vals)
Claude Haiku 5.5—
Qwen3.8 Max67.4%
Source
Not directly comparable

Coding

FrontierCode 1.1 Main
Claude Haiku 5.546.4%
Source
Qwen3.8 Max—
Not directly comparable
Terminal-Bench 2.1
Claude Haiku 5.5—
Qwen3.8 Max86.6%
Source
Not directly comparable
SWE-bench Pro
Claude Haiku 5.5—
Qwen3.8 Max67.7%
Source
Not directly comparable
DeepSWE
Claude Haiku 5.5—
Qwen3.8 Max56.6%
Source
Not directly comparable
NL2Repo
Claude Haiku 5.5—
Qwen3.8 Max55.9%
Source
Not directly comparable
FrontierSWE
Claude Haiku 5.5—
Qwen3.8 Max73.5%
Source
Not directly comparable
MLS-Bench Lite
Claude Haiku 5.5—
Qwen3.8 Max41.0%
Source
Not directly comparable
PaperBench
Claude Haiku 5.5—
Qwen3.8 Max93.0%
Source
Not directly comparable
VulcanBench v3
Claude Haiku 5.5—
Qwen3.8 Max81.2%
Source
Not directly comparable
OpenHarmony Bench
Claude Haiku 5.5—
Qwen3.8 Max60.8%
Source
Not directly comparable
FrontierSWE v2
Claude Haiku 5.5—
Qwen3.8 Max15.8%
Source
Not directly comparable
LiveCodeBench (Vals)
Claude Haiku 5.5—
Qwen3.8 Max87.9%
Source
Not directly comparable
SWE-bench (Vals)
Claude Haiku 5.5—
Qwen3.8 Max85.6%
Source
Not directly comparable

Reasoning

MRCRv2
Claude Haiku 5.5—
Qwen3.8 Max92.9%
Source
Not directly comparable
LongBench v2
Claude Haiku 5.5—
Qwen3.8 Max66.3%
Source
Not directly comparable

Multimodal

Chartography (no tools)
Claude Haiku 5.546.4%
Source
Qwen3.8 Max—
Not directly comparable
MMMU-Pro
Claude Haiku 5.5—
Qwen3.8 Max82.3%
Source
Not directly comparable
MathVision
Claude Haiku 5.5—
Qwen3.8 Max95.2%
Source
Not directly comparable
MathVision w/ Python
Claude Haiku 5.5—
Qwen3.8 Max97.7%
Source
Not directly comparable
BabyVision
Claude Haiku 5.5—
Qwen3.8 Max82.0%
Source
Not directly comparable
BabyVision w/ Python
Claude Haiku 5.5—
Qwen3.8 Max91.3%
Source
Not directly comparable
ZeroBench
Claude Haiku 5.5—
Qwen3.8 Max24.0%
Source
Not directly comparable
ZeroBench w/ Python
Claude Haiku 5.5—
Qwen3.8 Max49.0%
Source
Not directly comparable
MedXpertQA (MM)
Claude Haiku 5.5—
Qwen3.8 Max80.4%
Source
Not directly comparable
ScreenSpot Pro
Claude Haiku 5.5—
Qwen3.8 Max84.5%
Source
Not directly comparable
Vision2Web
Claude Haiku 5.5—
Qwen3.8 Max69.0%
Source
Not directly comparable
CharXiv w/o tools
Claude Haiku 5.5—
Qwen3.8 Max88.4%
Source
Not directly comparable
CharXiv
Claude Haiku 5.5—
Qwen3.8 Max93.5%
Source
Not directly comparable
OmniDocBench 1.5
Claude Haiku 5.5—
Qwen3.8 Max92.1%
Source
Not directly comparable
OCRBench V2
Claude Haiku 5.5—
Qwen3.8 Max74.2%
Source
Not directly comparable
CC-OCR
Claude Haiku 5.5—
Qwen3.8 Max79.6%
Source
Not directly comparable
RealWorldQA
Claude Haiku 5.5—
Qwen3.8 Max88.0%
Source
Not directly comparable
ERQA
Claude Haiku 5.5—
Qwen3.8 Max77.8%
Source
Not directly comparable
SimpleVQA
Claude Haiku 5.5—
Qwen3.8 Max75.0%
Source
Not directly comparable
PerceptionBench
Claude Haiku 5.5—
Qwen3.8 Max63.5%
Source
Not directly comparable
Video-MME (with subtitle)
Claude Haiku 5.5—
Qwen3.8 Max90.4%
Source
Not directly comparable
VideoMMMU
Claude Haiku 5.5—
Qwen3.8 Max88.7%
Source
Not directly comparable
MMVU
Claude Haiku 5.5—
Qwen3.8 Max82.4%
Source
Not directly comparable
MLVU (M-Avg)
Claude Haiku 5.5—
Qwen3.8 Max90.8%
Source
Not directly comparable
LVBench
Claude Haiku 5.5—
Qwen3.8 Max81.8%
Source
Not directly comparable

Knowledge

HLE w/o tools
Claude Haiku 5.545.9%
Source
Qwen3.8 Max43.6%
Source
Claude Haiku 5.5 leads this result
GPQA
Claude Haiku 5.5—
Qwen3.8 Max92.6%
Source
Not directly comparable
GPQA-D
Claude Haiku 5.5—
Qwen3.8 Max92.6%
Source
Not directly comparable
HLE
Claude Haiku 5.5—
Qwen3.8 Max43.6%
Source
Not directly comparable
GPQA Diamond (Vals)
Claude Haiku 5.5—
Qwen3.8 Max93.7%
Source
Not directly comparable
MMLU-Pro (Vals)
Claude Haiku 5.5—
Qwen3.8 Max88.6%
Source
Not directly comparable

Instruction following

IFBench
Claude Haiku 5.5—
Qwen3.8 Max82.8%
Source
Not directly comparable

63 public results · 2 shared

Related comparisons

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Last updated October 7, 2026

Claude Haiku 5.5 vs Qwen3.8 Max

Decision reading

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, Claude Haiku 5.5 or Qwen3.8 Max?

Which is better for coding, Claude Haiku 5.5 or Qwen3.8 Max?

Which is better for agentic tasks, Claude Haiku 5.5 or Qwen3.8 Max?

Which costs less, Claude Haiku 5.5 or Qwen3.8 Max?

Which has the larger context window, Claude Haiku 5.5 or Qwen3.8 Max?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Instruction following

Related comparisons

Watch Claude Haiku 5.5 vs Qwen3.8 Max