Agentic
Directional only- Claude Opus 4.7 (Adaptive)
- 61.0
- Supported · #21/151
- Qwen3.5-122B-A10B
- 49.3
- Estimated · #69/151
- Basis
- BenchAlign lane · 7 vs 3 public rows
- Reading
- Directional only
Anthropic
69.94/100
Estimated · Public rank #23
90% interval 51.6–81.5
Claude Opus 4.7 (Adaptive) vs Qwen3.5-122B-A10B
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Opus 4.7 (Adaptive) has the higher public score estimate, 69.94 versus 59.01, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
6 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.
Long documents
Prompts that approach the documented context limit
Claude Opus 4.7 (Adaptive)
Claude Opus 4.7 (Adaptive) 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
Claude Opus 4.7 (Adaptive) is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
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
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
15 Claude Opus 4.7 (Adaptive) only
6 Shared
9 Qwen3.5-122B-A10B only
- Shared results
- 6
- Claude Opus 4.7 (Adaptive) only
- 15
- Qwen3.5-122B-A10B only
- 9
- Like-for-like categories
- 0 / 8
4 categories rest 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
Directional only- Claude Opus 4.7 (Adaptive)
- 59.6
- Estimated · #27/183
- Qwen3.5-122B-A10B
- 44.2
- Supported · #114/183
- Basis
- BenchAlign lane · 3 vs 1 public rows
- Reading
- Directional only
Knowledge
Directional only- Claude Opus 4.7 (Adaptive)
- 61.9
- Estimated · #31/181
- Qwen3.5-122B-A10B
- 50.2
- Supported · #89/181
- Basis
- BenchAlign lane · 4 vs 3 public rows
- Reading
- Directional only
Multimodal
Directional only- Claude Opus 4.7 (Adaptive)
- 50.3
- #36/48
- Qwen3.5-122B-A10B
- 57.0
- #32/48
- Basis
- Provisional lane · 2 vs 1 weighted rows
- Reading
- Directional only
Reasoning
Not comparable- Claude Opus 4.7 (Adaptive)
- 49.7
- Unranked · 3 rankable rows
- Qwen3.5-122B-A10B
- 47.9
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 2 vs 1 weighted rows
- Reading
- Not comparable
Math
Not comparable- Claude Opus 4.7 (Adaptive)
- Not ranked
- Qwen3.5-122B-A10B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Opus 4.7 (Adaptive)
- Not ranked
- Qwen3.5-122B-A10B
- 36.8
- #10/12
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Opus 4.7 (Adaptive)
- Not ranked
- Qwen3.5-122B-A10B
- 92.7
- #11/120
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Claude Opus 4.7 (Adaptive) | Qwen3.5-122B-A10B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 61.0Supported · #21/151 | 49.3Estimated · #69/151 | Directional onlyBenchAlign lane · 7 vs 3 public rows | Directional only |
| Coding | 59.6Estimated · #27/183 | 44.2Supported · #114/183 | Directional onlyBenchAlign lane · 3 vs 1 public rows | Directional only |
| Knowledge | 61.9Estimated · #31/181 | 50.2Supported · #89/181 | Directional onlyBenchAlign lane · 4 vs 3 public rows | Directional only |
| Multimodal | 50.3#36/48 | 57.0#32/48 | Directional onlyProvisional lane · 2 vs 1 weighted rows | Directional only |
| Reasoning | 49.7Unranked · 3 rankable rows | 47.9Unranked · 3 rankable rows | Not comparableProvisional lane · 2 vs 1 weighted rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | 36.8#10/12 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Instruction following | Not ranked | 92.7#11/120 | 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.
Terminal-Bench 2.0
Agentic
Claude Opus 4.7 (Adaptive): 69.4%Qwen3.5-122B-A10B: 49.4%Normalized gap 20.0Claude Opus 4.7 (Adaptive) source Qwen3.5-122B-A10B sourceOSWorld-Verified
Agentic
Claude Opus 4.7 (Adaptive): 78%Qwen3.5-122B-A10B: 58%Normalized gap 20.0Claude Opus 4.7 (Adaptive) source Qwen3.5-122B-A10B sourceSWE-bench Verified
Coding
Claude Opus 4.7 (Adaptive): 87.6%Qwen3.5-122B-A10B: 72%Normalized gap 15.6Claude Opus 4.7 (Adaptive) source Qwen3.5-122B-A10B sourceBrowseComp
Agentic
Claude Opus 4.7 (Adaptive): 79.3%Qwen3.5-122B-A10B: 63.8%Normalized gap 15.5Claude Opus 4.7 (Adaptive) source Qwen3.5-122B-A10B sourceCharXiv
Multimodal
Claude Opus 4.7 (Adaptive): 91%Qwen3.5-122B-A10B: 77.2%Normalized gap 13.8Claude Opus 4.7 (Adaptive) source Qwen3.5-122B-A10B 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 Opus 4.7 (Adaptive)
- $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 4.7 (Adaptive)
- $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 4.7 (Adaptive)
- $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 4.7 (Adaptive) 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.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Opus 4.7 (Adaptive)Qwen3.5-122B-A10B
Context window
Maximum documented context; output-token limits may be lower.
Claude Opus 4.7 (Adaptive)
1M
Qwen3.5-122B-A10B
262K
API model ID
Claude Opus 4.7 (Adaptive)
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 4.7 (Adaptive)
Not published
Qwen3.5-122B-A10B
No comparable hosted API rate
Documented inputs
Claude Opus 4.7 (Adaptive)
Not sourced
Qwen3.5-122B-A10B
Not sourced
Documented outputs
Claude Opus 4.7 (Adaptive)
Not sourced
Qwen3.5-122B-A10B
Not sourced
Provider availability
Claude Opus 4.7 (Adaptive)
Not sourced
Qwen3.5-122B-A10B
Not sourced
Reasoning profile
Claude Opus 4.7 (Adaptive)
Reasoning
Qwen3.5-122B-A10B
Reasoning
Weight access
Claude Opus 4.7 (Adaptive)
Proprietary
Qwen3.5-122B-A10B
Open Weight
License
Claude Opus 4.7 (Adaptive)
Proprietary
Qwen3.5-122B-A10B
Open Weight
Release date
Claude Opus 4.7 (Adaptive)
2026-04-16
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 4.7 (Adaptive) has the higher public score estimate, 69.94 versus 59.01, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Claude Opus 4.7 (Adaptive) 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 evidence30 rows
Agentic
Terminal-Bench 2.0
Claude Opus 4.7 (Adaptive)69.4%SourceQwen3.5-122B-A10B49.4%SourceClaude Opus 4.7 (Adaptive) leads this result
BrowseComp
Claude Opus 4.7 (Adaptive)79.3%SourceQwen3.5-122B-A10B63.8%SourceClaude Opus 4.7 (Adaptive) leads this result
MCP Atlas
Claude Opus 4.7 (Adaptive)77.3%SourceQwen3.5-122B-A10B—Not directly comparable
OSWorld-Verified
Claude Opus 4.7 (Adaptive)78%SourceQwen3.5-122B-A10B58%SourceClaude Opus 4.7 (Adaptive) leads this result
CyberGym
Claude Opus 4.7 (Adaptive)73.1%SourceQwen3.5-122B-A10B—Not directly comparable
OSWorld 2.0
Claude Opus 4.7 (Adaptive)18.2%SourceQwen3.5-122B-A10B—Not directly comparable
JobBench
Claude Opus 4.7 (Adaptive)45.9%SourceQwen3.5-122B-A10B—Not directly comparable
Coding
SWE-bench Verified
Claude Opus 4.7 (Adaptive)87.6%SourceQwen3.5-122B-A10B72%SourceClaude Opus 4.7 (Adaptive) leads this result
SWE-bench Pro
Claude Opus 4.7 (Adaptive)64.3%SourceQwen3.5-122B-A10B—Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.7 (Adaptive)69.4%SourceQwen3.5-122B-A10B—Not directly comparable
Reasoning
MRCR v2 128K-256K
Claude Opus 4.7 (Adaptive)59.2%SourceQwen3.5-122B-A10B—Not directly comparable
ARC-AGI-2
Claude Opus 4.7 (Adaptive)75.8%SourceQwen3.5-122B-A10B—Not directly comparable
ARC-AGI-3
Claude Opus 4.7 (Adaptive)0.2%SourceQwen3.5-122B-A10B—Not directly comparable
LongBench v2
Claude Opus 4.7 (Adaptive)—Qwen3.5-122B-A10B60.2%SourceNot directly comparable
Knowledge
GPQA
Claude Opus 4.7 (Adaptive)94.2%SourceQwen3.5-122B-A10B86.6%SourceClaude Opus 4.7 (Adaptive) leads this result
GPQA-D
Claude Opus 4.7 (Adaptive)94.2%SourceQwen3.5-122B-A10B—Not directly comparable
HLE
Claude Opus 4.7 (Adaptive)54.7%SourceQwen3.5-122B-A10B—Not directly comparable
HLE w/o tools
Claude Opus 4.7 (Adaptive)46.9%SourceQwen3.5-122B-A10B—Not directly comparable
MMLU-Pro
Claude Opus 4.7 (Adaptive)—Qwen3.5-122B-A10B86.7%SourceNot directly comparable
SuperGPQA
Claude Opus 4.7 (Adaptive)—Qwen3.5-122B-A10B67.1%SourceNot directly comparable
Math
FrontierMath (legacy)
Claude Opus 4.7 (Adaptive)43.8%SourceQwen3.5-122B-A10B—Not directly comparable
Multilingual
MMLU-ProX
Claude Opus 4.7 (Adaptive)—Qwen3.5-122B-A10B82.2%SourceNot directly comparable
Multimodal
OfficeQA Pro
Claude Opus 4.7 (Adaptive)43.6%SourceQwen3.5-122B-A10B—Not directly comparable
CharXiv
Claude Opus 4.7 (Adaptive)91%SourceQwen3.5-122B-A10B77.2%SourceClaude Opus 4.7 (Adaptive) leads this result
CharXiv w/o tools
Claude Opus 4.7 (Adaptive)82.1%SourceQwen3.5-122B-A10B—Not directly comparable
MMMU
Claude Opus 4.7 (Adaptive)—Qwen3.5-122B-A10B83.9%SourceNot directly comparable
MMVU
Claude Opus 4.7 (Adaptive)—Qwen3.5-122B-A10B74.7%SourceNot directly comparable
MathVision
Claude Opus 4.7 (Adaptive)—Qwen3.5-122B-A10B86.2%SourceNot directly comparable
V*
Claude Opus 4.7 (Adaptive)—Qwen3.5-122B-A10B93.2%SourceNot directly comparable
Instruction following
IFEval
Claude Opus 4.7 (Adaptive)—Qwen3.5-122B-A10B93.4%SourceNot directly comparable
Frequently asked questions
Which is better, Claude Opus 4.7 (Adaptive) or Qwen3.5-122B-A10B?
Claude Opus 4.7 (Adaptive) has the higher public score estimate, 69.94 versus 59.01, 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 4.7 (Adaptive) or Qwen3.5-122B-A10B?
Claude Opus 4.7 (Adaptive) scores higher for coding on the public lane, 59.6 to 44.2. Claude Opus 4.7 (Adaptive) is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, Claude Opus 4.7 (Adaptive) or Qwen3.5-122B-A10B?
Claude Opus 4.7 (Adaptive) scores higher for agentic tasks on the public lane, 61 to 49.3. 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 4.7 (Adaptive) 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 4.7 (Adaptive) or Qwen3.5-122B-A10B?
Claude Opus 4.7 (Adaptive) has the larger documented context window: 1M, compared with 262K.
Related comparisons
Last updated September 4, 2026
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