Claude Opus 4.6 vs Qwen3.5-122B-A10B

Updated September 27, 2026. Rank says Claude Opus 4.6 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Claude Opus 4.6 has the higher public score estimate, 63.64 versus 40.06, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 7 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 Opus 4.6

Anthropic

63.64/100

Supported · Public rank #31

90% interval 51.6–75.6

Model B

Qwen3.5-122B-A10B

Alibaba

40.06/100

Estimated · Public rank #113

90% interval 19.5–60.6

Shared results: 7
Claude Opus 4.6 only: 27
Qwen3.5-122B-A10B only: 8
Like-for-like categories: 1 / 8

Supported: Claude Opus 4.6 · Estimated: Qwen3.5-122B-A10BHow 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 Opus 4.6
Claude Opus 4.6 leads on the public coding lane, 51.1 to 35.7, with Supported evidence for both models, although the 90% intervals overlap.
Confidence: limited
Long documents
Prompts that approach the documented context limit
Claude Opus 4.6
Claude Opus 4.6 has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Qwen3.5-122B-A10B is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
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
A complete comparable API-rate estimate is not available for both models.
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

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.

51.1Claude Opus 4.635.7Qwen3.5-122B-A10B

Like-for-like · BenchAlign v5.7

Claude Opus 4.6 leads the like-for-like coding row, although the 90% intervals overlap.

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.

SuperGPQAKnowledge
Normalized gap 27.9
Claude Opus 4.6:95%
Qwen3.5-122B-A10B:67.1%
Claude Opus 4.6 source Qwen3.5-122B-A10B source
BrowseCompAgentic
Normalized gap 19.9
Claude Opus 4.6:83.7%
Qwen3.5-122B-A10B:63.8%
Claude Opus 4.6 source Qwen3.5-122B-A10B source
Terminal-Bench 2.0Agentic
Normalized gap 16.0
Claude Opus 4.6:65.4%
Qwen3.5-122B-A10B:49.4%
Claude Opus 4.6 source Qwen3.5-122B-A10B source
OSWorld-VerifiedAgentic
Normalized gap 14.7
Claude Opus 4.6:72.7%
Qwen3.5-122B-A10B:58%
Claude Opus 4.6 source Qwen3.5-122B-A10B source
SWE-bench VerifiedCoding
Normalized gap 8.8
Claude Opus 4.6:80.8%
Qwen3.5-122B-A10B:72%
Claude Opus 4.6 source Qwen3.5-122B-A10B 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 v5.7 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 Opus 4.6: 51.1; Supported · #36/135
Qwen3.5-122B-A10B: 35.7; Supported · #73/135
Basis: BenchAlign v5.7 lane · 8 vs 1 public rows
Reading: Claude Opus 4.6 leads · intervals overlap

Agentic

Directional only

Claude Opus 4.6: 44.3; Supported · #39/105
Qwen3.5-122B-A10B: 23.1; Estimated · #84/105
Basis: BenchAlign v5.7 lane · 10 vs 3 public rows
Reading: Directional only

Multimodal

Directional only

Claude Opus 4.6: 59.6; #30/50
Qwen3.5-122B-A10B: 57.0; #34/50
Basis: Provisional lane · 1 vs 1 weighted rows
Reading: Directional only

Knowledge

Directional only

Claude Opus 4.6: 58.7; Estimated · #37/158
Qwen3.5-122B-A10B: 41.5; Supported · #86/158
Basis: BenchAlign v5.7 lane · 9 vs 3 public rows
Reading: Directional only

Instruction following

Directional only

Claude Opus 4.6: 51.0; #79/124
Qwen3.5-122B-A10B: 91.6; #11/124
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Directional only

Reasoning

Not comparable

Claude Opus 4.6: 68.1; Unranked · 2 rankable rows
Qwen3.5-122B-A10B: 49.8; Unranked · 3 rankable rows
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Claude Opus 4.6: Not ranked
Qwen3.5-122B-A10B: 36.8; #10/12
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Claude Opus 4.6: 58.5; Unranked · 3 rankable rows
Qwen3.5-122B-A10B: Not ranked
Basis: Provisional lane · 2 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Claude Opus 4.6 and Qwen3.5-122B-A10B
Category	Claude Opus 4.6	Qwen3.5-122B-A10B	Basis	Reading
Coding	51.1Supported · #36/135	35.7Supported · #73/135	Like-for-likeBenchAlign v5.7 lane · 8 vs 1 public rows	Claude Opus 4.6 leads · intervals overlap
Agentic	44.3Supported · #39/105	23.1Estimated · #84/105	Directional onlyBenchAlign v5.7 lane · 10 vs 3 public rows	Directional only
Multimodal	59.6#30/50	57.0#34/50	Directional onlyProvisional lane · 1 vs 1 weighted rows	Directional only
Knowledge	58.7Estimated · #37/158	41.5Supported · #86/158	Directional onlyBenchAlign v5.7 lane · 9 vs 3 public rows	Directional only
Instruction following	51.0#79/124	91.6#11/124	Directional onlyProvisional lane · 0 vs 0 weighted rows	Directional only
Reasoning	68.1Unranked · 2 rankable rows	49.8Unranked · 3 rankable rows	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multilingual	Not ranked	36.8#10/12	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	58.5Unranked · 3 rankable rows	Not ranked	Not comparableProvisional lane · 2 vs 0 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) 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 Opus 4.6: $0.0175; Fits in one request
Qwen3.5-122B-A10B: Self-hosted; infrastructure cost varies; Fits in one request

Qwen3.5-122B-A10B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Opus 4.6: $0.325; Fits in one request
Qwen3.5-122B-A10B: Self-hosted; infrastructure cost varies; Fits in one request

Qwen3.5-122B-A10B has no comparable published API token rate.

Cache-heavy agent loop

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

Claude Opus 4.6: $1.35; Fits in one request; Cached input priced at the published list-input rate
Qwen3.5-122B-A10B: Self-hosted; infrastructure cost varies; Fits in one request; Cached-input rate unavailable

Claude Opus 4.6 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.5-122B-A10B 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 Opus 4.6Qwen3.5-122B-A10B

Context window

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

Claude Opus 4.6

Qwen3.5-122B-A10B

262K

API model ID

Claude Opus 4.6

Not sourced

Qwen3.5-122B-A10B

Not sourced

Cached-input rate

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

Claude Opus 4.6

Not published

Qwen3.5-122B-A10B

No comparable hosted API rate

Documented inputs

Claude Opus 4.6

Not sourced

Qwen3.5-122B-A10B

Not sourced

Documented outputs

Claude Opus 4.6

Not sourced

Qwen3.5-122B-A10B

Not sourced

Provider availability

Claude Opus 4.6

Not sourced

Qwen3.5-122B-A10B

Not sourced

Reasoning profile

Claude Opus 4.6

Non-Reasoning

Qwen3.5-122B-A10B

Reasoning

Weight access

Claude Opus 4.6

Proprietary

Qwen3.5-122B-A10B

Open Weight

License

Claude Opus 4.6

Proprietary

Qwen3.5-122B-A10B

Open Weight

Release date

Claude Opus 4.6

2026-02-01

Qwen3.5-122B-A10B

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 Opus 4.6 has the higher public score estimate, 63.64 versus 40.06, but the 90% score intervals overlap.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Claude Opus 4.6 has the larger documented window (1M).

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

Questions

Which is better, Claude Opus 4.6 or Qwen3.5-122B-A10B?

Claude Opus 4.6 has the higher public score estimate, 63.64 versus 40.06, 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 Opus 4.6 or Qwen3.5-122B-A10B?

Claude Opus 4.6 leads the public coding lane, 51.1 to 35.7, with Supported evidence for both models, although the 90% intervals overlap.

Which is better for agentic tasks, Claude Opus 4.6 or Qwen3.5-122B-A10B?

Claude Opus 4.6 scores higher for agentic tasks on the public lane, 44.3 to 23.1. Qwen3.5-122B-A10B is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Claude Opus 4.6 or Qwen3.5-122B-A10B?

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 Opus 4.6 or Qwen3.5-122B-A10B?

Claude Opus 4.6 has the larger documented context window: 1M, compared with 262K.

Benchmark evidence

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

Browse raw public benchmark evidence42 rows

Agentic

Terminal-Bench 2.0
Claude Opus 4.665.4%
Source
Qwen3.5-122B-A10B49.4%
Source
Claude Opus 4.6 leads this result
BrowseComp
Claude Opus 4.683.7%
Source
Qwen3.5-122B-A10B63.8%
Source
Claude Opus 4.6 leads this result
OSWorld-Verified
Claude Opus 4.672.7%
Source
Qwen3.5-122B-A10B58%
Source
Claude Opus 4.6 leads this result
Claw-Eval
Claude Opus 4.670.4%
Source
Qwen3.5-122B-A10B—
Not directly comparable
DeepSearchQA
Claude Opus 4.673.7%
Source
Qwen3.5-122B-A10B—
Not directly comparable
CyberGym
Claude Opus 4.666.6%
Source
Qwen3.5-122B-A10B—
Not directly comparable
Gert Labs
Claude Opus 4.661.85%
Source
Qwen3.5-122B-A10B—
Not directly comparable
ResearchClawBench
Claude Opus 4.619.9%
Source
Qwen3.5-122B-A10B—
Not directly comparable
JobBench
Claude Opus 4.636.7%
Source
Qwen3.5-122B-A10B—
Not directly comparable
ApprenticeBench
Claude Opus 4.65%
Source
Qwen3.5-122B-A10B—
Not directly comparable

Coding

SWE-bench Verified
Claude Opus 4.680.8%
Source
Qwen3.5-122B-A10B72%
Source
Claude Opus 4.6 leads this result
SWE-bench Verified*
Claude Opus 4.675.6%
Source
Qwen3.5-122B-A10B—
Not directly comparable
LiveCodeBench Pro
Claude Opus 4.670.7%
Source
Qwen3.5-122B-A10B—
Not directly comparable
SWE-bench Pro
Claude Opus 4.653.4%
Source
Qwen3.5-122B-A10B—
Not directly comparable
SWE-Rebench
Claude Opus 4.665.3%
Source
Qwen3.5-122B-A10B—
Not directly comparable
React Native Evals
Claude Opus 4.684.1%
Source
Qwen3.5-122B-A10B—
Not directly comparable
Vibe Code Bench
Claude Opus 4.657.57%
Source
Qwen3.5-122B-A10B—
Not directly comparable
FrontierCode 1.1 Main
Claude Opus 4.626.9%
Source
Qwen3.5-122B-A10B—
Not directly comparable

Reasoning

LongBench v2
Claude Opus 4.6—
Qwen3.5-122B-A10B60.2%
Source
Not directly comparable

Multimodal

MMMU-Pro
Claude Opus 4.677.3%
Source
Qwen3.5-122B-A10B—
Not directly comparable
ERQA
Claude Opus 4.651.6%
Source
Qwen3.5-122B-A10B—
Not directly comparable
ScreenSpot Pro
Claude Opus 4.683.1%
Source
Qwen3.5-122B-A10B—
Not directly comparable
MedXpertQA (MM)
Claude Opus 4.664.8%
Source
Qwen3.5-122B-A10B—
Not directly comparable
MMMU
Claude Opus 4.6—
Qwen3.5-122B-A10B83.9%
Source
Not directly comparable
MMVU
Claude Opus 4.6—
Qwen3.5-122B-A10B74.7%
Source
Not directly comparable
MathVision
Claude Opus 4.6—
Qwen3.5-122B-A10B86.2%
Source
Not directly comparable
CharXiv
Claude Opus 4.6—
Qwen3.5-122B-A10B77.2%
Source
Not directly comparable
V*
Claude Opus 4.6—
Qwen3.5-122B-A10B93.2%
Source
Not directly comparable

Knowledge

GPQA
Claude Opus 4.691.3%
Source
Qwen3.5-122B-A10B86.6%
Source
Claude Opus 4.6 leads this result
GPQA-D
Claude Opus 4.689.2%
Source
Qwen3.5-122B-A10B—
Not directly comparable
SuperGPQA
Claude Opus 4.695%
Source
Qwen3.5-122B-A10B67.1%
Source
Claude Opus 4.6 leads this result
MMLU-Pro
Claude Opus 4.682%
Source
Qwen3.5-122B-A10B86.7%
Source
Qwen3.5-122B-A10B leads this result
MMLU-Pro (Arcee)
Claude Opus 4.689.1%
Source
Qwen3.5-122B-A10B—
Not directly comparable
HLE
Claude Opus 4.653%
Source
Qwen3.5-122B-A10B—
Not directly comparable
HLE w/o tools
Claude Opus 4.640%
Source
Qwen3.5-122B-A10B—
Not directly comparable
HealthBench Hard
Claude Opus 4.614.8%
Source
Qwen3.5-122B-A10B—
Not directly comparable
MedXpertQA (Text)
Claude Opus 4.652.1%
Source
Qwen3.5-122B-A10B—
Not directly comparable

Multilingual

MMLU-ProX
Claude Opus 4.6—
Qwen3.5-122B-A10B82.2%
Source
Not directly comparable

Instruction following

IFEval
Claude Opus 4.6—
Qwen3.5-122B-A10B93.4%
Source
Not directly comparable

Math

AIME25 (Arcee)
Claude Opus 4.699.8%
Source
Qwen3.5-122B-A10B—
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Claude Opus 4.640.700%
Source
Qwen3.5-122B-A10B—
Not directly comparable
FrontierMath v2 (Tier 4)
Claude Opus 4.622.900%
Source
Qwen3.5-122B-A10B—
Not directly comparable

42 public results · 7 shared

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Last updated September 27, 2026

Claude Opus 4.6 vs Qwen3.5-122B-A10B

Decision reading

Which one for your work

Coding work

Long documents

Agentic work

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

Coding

Agentic

Multimodal

Knowledge

Instruction following

Reasoning

Multilingual

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 Opus 4.6 or Qwen3.5-122B-A10B?

Which is better for coding, Claude Opus 4.6 or Qwen3.5-122B-A10B?

Which is better for agentic tasks, Claude Opus 4.6 or Qwen3.5-122B-A10B?

Which costs less, Claude Opus 4.6 or Qwen3.5-122B-A10B?

Which has the larger context window, Claude Opus 4.6 or Qwen3.5-122B-A10B?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

Related comparisons

Watch Claude Opus 4.6 vs Qwen3.5-122B-A10B