Agentic
Directional only- GPT-5.5 Pro
- 60.6
- Estimated · #24/151
- Qwen3.6-35B-A3B
- 44.4
- Estimated · #102/151
- Basis
- BenchAlign lane · 1 vs 11 public rows
- Reading
- Directional only
GPT-5.5 Pro vs Qwen3.6-35B-A3B
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
GPT-5.5 Pro has the higher public score estimate, 63.07 versus 48.34, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
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.
Long documents
Prompts that approach the documented context limit
GPT-5.5 Pro
GPT-5.5 Pro 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
GPT-5.5 Pro is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
GPT-5.5 Pro and Qwen3.6-35B-A3B are 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.
5 GPT-5.5 Pro only
1 Shared
40 Qwen3.6-35B-A3B only
- Shared results
- 1
- GPT-5.5 Pro only
- 5
- Qwen3.6-35B-A3B only
- 40
- Like-for-like categories
- 0 / 8
2 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.
Knowledge
Directional only- GPT-5.5 Pro
- 61.1
- Estimated · #36/181
- Qwen3.6-35B-A3B
- 46.5
- Estimated · #109/181
- Basis
- BenchAlign lane · 2 vs 5 public rows
- Reading
- Directional only
Coding
Not comparable- GPT-5.5 Pro
- Not ranked
- Qwen3.6-35B-A3B
- 47.3
- Estimated · #90/183
- Basis
- BenchAlign lane · 0 vs 6 public rows
- Reading
- Not comparable
Reasoning
Not comparable- GPT-5.5 Pro
- Not ranked
- Qwen3.6-35B-A3B
- 69.0
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- GPT-5.5 Pro
- 70.2
- Unranked · 3 rankable rows
- Qwen3.6-35B-A3B
- 71.5
- Unranked · 5 rankable rows
- Basis
- Provisional lane · 2 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-5.5 Pro
- Not ranked
- Qwen3.6-35B-A3B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- GPT-5.5 Pro
- Not ranked
- Qwen3.6-35B-A3B
- 50.1
- #37/48
- Basis
- Provisional lane · 0 vs 2 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- GPT-5.5 Pro
- Not ranked
- Qwen3.6-35B-A3B
- 78.0
- #55/120
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | GPT-5.5 Pro | Qwen3.6-35B-A3B | Basis | Reading |
|---|---|---|---|---|
| Agentic | 60.6Estimated · #24/151 | 44.4Estimated · #102/151 | Directional onlyBenchAlign lane · 1 vs 11 public rows | Directional only |
| Knowledge | 61.1Estimated · #36/181 | 46.5Estimated · #109/181 | Directional onlyBenchAlign lane · 2 vs 5 public rows | Directional only |
| Coding | Not ranked | 47.3Estimated · #90/183 | Not comparableBenchAlign lane · 0 vs 6 public rows | Not comparable |
| Reasoning | Not ranked | 69.0Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Math | 70.2Unranked · 3 rankable rows | 71.5Unranked · 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 | 50.1#37/48 | Not comparableProvisional lane · 0 vs 2 weighted rows | Not comparable |
| Instruction following | Not ranked | 78.0#55/120 | 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.
HLE
Knowledge
GPT-5.5 Pro: 57.2%Qwen3.6-35B-A3B: 21.4%Normalized gap 35.8GPT-5.5 Pro source Qwen3.6-35B-A3B 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
- GPT-5.5 Pro
- $0.12
- Fits in one request
- Qwen3.6-35B-A3B
- API rate not published
- Fits in one request
Qwen3.6-35B-A3B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- GPT-5.5 Pro
- $2.04
- Fits in one request
- Qwen3.6-35B-A3B
- API rate not published
- Fits in one request
Qwen3.6-35B-A3B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GPT-5.5 Pro
- $8.40
- Fits in one request
- Cached input priced at the published list-input rate
- Qwen3.6-35B-A3B
- API rate not published
- Fits in one request
- Cached-input rate unavailable
GPT-5.5 Pro has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.6-35B-A3B 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.
SpecificationGPT-5.5 ProQwen3.6-35B-A3B
Context window
Maximum documented context; output-token limits may be lower.
GPT-5.5 Pro
Qwen3.6-35B-A3B
262K
API model ID
GPT-5.5 Pro
gpt-5.5-pro
OpenAI GPT-5.5 Pro model documentationQwen3.6-35B-A3B
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GPT-5.5 Pro
Not published
OpenAI pricingQwen3.6-35B-A3B
No comparable hosted API rate
Documented inputs
GPT-5.5 Pro
text, image
OpenAI model catalogQwen3.6-35B-A3B
Not sourced
Documented outputs
GPT-5.5 Pro
Qwen3.6-35B-A3B
Not sourced
Provider availability
GPT-5.5 Pro
Generally Available · OpenAI Responses API
OpenAI model catalogQwen3.6-35B-A3B
Not sourced
Reasoning profile
GPT-5.5 Pro
Reasoning
Qwen3.6-35B-A3B
Reasoning
Weight access
GPT-5.5 Pro
Proprietary
Qwen3.6-35B-A3B
Open Weight
License
GPT-5.5 Pro
Proprietary
Qwen3.6-35B-A3B
Open Weight
Release date
GPT-5.5 Pro
2026-04-23
Qwen3.6-35B-A3B
2026-04-15
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
- GPT-5.5 Pro has the higher public score estimate, 63.07 versus 48.34, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- GPT-5.5 Pro has the larger documented window (1.05M).
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
BrowseComp
GPT-5.5 Pro90.1%SourceQwen3.6-35B-A3B—Not directly comparable
Terminal-Bench 2.0
GPT-5.5 Pro—Qwen3.6-35B-A3B51.5%SourceNot directly comparable
Claw-Eval
GPT-5.5 Pro—Qwen3.6-35B-A3B68.7%SourceNot directly comparable
QwenClawBench
GPT-5.5 Pro—Qwen3.6-35B-A3B52.6%SourceNot directly comparable
QwenWebBench
GPT-5.5 Pro—Qwen3.6-35B-A3B1397SourceNot directly comparable
τ³-bench results
GPT-5.5 Pro—Qwen3.6-35B-A3B67.2%SourceNot directly comparable
VITA-Bench
GPT-5.5 Pro—Qwen3.6-35B-A3B35.6%SourceNot directly comparable
DeepPlanning
GPT-5.5 Pro—Qwen3.6-35B-A3B25.9%SourceNot directly comparable
Toolathlon
GPT-5.5 Pro—Qwen3.6-35B-A3B26.9%SourceNot directly comparable
MCP Atlas
GPT-5.5 Pro—Qwen3.6-35B-A3B62.8%SourceNot directly comparable
WideResearch
GPT-5.5 Pro—Qwen3.6-35B-A3B60.1%SourceNot directly comparable
Gert Labs
GPT-5.5 Pro—Qwen3.6-35B-A3B42.65%SourceNot directly comparable
Coding
SWE-bench Verified
GPT-5.5 Pro—Qwen3.6-35B-A3B73.4%SourceNot directly comparable
SWE Multilingual
GPT-5.5 Pro—Qwen3.6-35B-A3B67.2%SourceNot directly comparable
SWE-bench Pro
GPT-5.5 Pro—Qwen3.6-35B-A3B49.5%SourceNot directly comparable
Terminal-Bench 2.0
GPT-5.5 Pro—Qwen3.6-35B-A3B51.5%SourceNot directly comparable
LiveCodeBench
GPT-5.5 Pro—Qwen3.6-35B-A3B80.4%SourceNot directly comparable
NL2Repo
GPT-5.5 Pro—Qwen3.6-35B-A3B29.4%SourceNot directly comparable
Knowledge
HLE
GPT-5.5 Pro57.2%SourceQwen3.6-35B-A3B21.4%SourceGPT-5.5 Pro leads this result
HLE w/o tools
GPT-5.5 Pro43.1%SourceQwen3.6-35B-A3B—Not directly comparable
MMLU-Pro
GPT-5.5 Pro—Qwen3.6-35B-A3B85.2%SourceNot directly comparable
SuperGPQA
GPT-5.5 Pro—Qwen3.6-35B-A3B64.7%SourceNot directly comparable
C-Eval
GPT-5.5 Pro—Qwen3.6-35B-A3B90%SourceNot directly comparable
GPQA
GPT-5.5 Pro—Qwen3.6-35B-A3B86%SourceNot directly comparable
Math
FrontierMath (legacy)
GPT-5.5 Pro52.4%SourceQwen3.6-35B-A3B—Not directly comparable
FrontierMath v2 (Tiers 1-3)
GPT-5.5 Pro51.000%SourceQwen3.6-35B-A3B—Not directly comparable
FrontierMath v2 (Tier 4)
GPT-5.5 Pro39.600%SourceQwen3.6-35B-A3B—Not directly comparable
HMMT Feb 2025
GPT-5.5 Pro—Qwen3.6-35B-A3B90.7%SourceNot directly comparable
HMMT Nov 2025
GPT-5.5 Pro—Qwen3.6-35B-A3B89.1%SourceNot directly comparable
HMMT Feb 2026
GPT-5.5 Pro—Qwen3.6-35B-A3B83.6%SourceNot directly comparable
MMAnswerBench
GPT-5.5 Pro—Qwen3.6-35B-A3B78.9%SourceNot directly comparable
AIME26
GPT-5.5 Pro—Qwen3.6-35B-A3B92.7%SourceNot directly comparable
Multimodal
MMMU
GPT-5.5 Pro—Qwen3.6-35B-A3B81.7%SourceNot directly comparable
MMMU-Pro
GPT-5.5 Pro—Qwen3.6-35B-A3B75.3%SourceNot directly comparable
RealWorldQA
GPT-5.5 Pro—Qwen3.6-35B-A3B85.3%SourceNot directly comparable
OmniDocBench 1.5
GPT-5.5 Pro—Qwen3.6-35B-A3B89.9%SourceNot directly comparable
CharXiv
GPT-5.5 Pro—Qwen3.6-35B-A3B78%SourceNot directly comparable
SimpleVQA
GPT-5.5 Pro—Qwen3.6-35B-A3B58.9%SourceNot directly comparable
CC-OCR
GPT-5.5 Pro—Qwen3.6-35B-A3B81.9%SourceNot directly comparable
AI2D_TEST
GPT-5.5 Pro—Qwen3.6-35B-A3B92.7%SourceNot directly comparable
RefCOCO (avg)
GPT-5.5 Pro—Qwen3.6-35B-A3B92.0%SourceNot directly comparable
ODINW13
GPT-5.5 Pro—Qwen3.6-35B-A3B50.8%SourceNot directly comparable
Video-MME (with subtitle)
GPT-5.5 Pro—Qwen3.6-35B-A3B86.6%SourceNot directly comparable
Video-MME (w/o subtitle)
GPT-5.5 Pro—Qwen3.6-35B-A3B82.5%SourceNot directly comparable
VideoMMMU
GPT-5.5 Pro—Qwen3.6-35B-A3B83.7%SourceNot directly comparable
MLVU (M-Avg)
GPT-5.5 Pro—Qwen3.6-35B-A3B86.2%SourceNot directly comparable
Frequently asked questions
Which is better, GPT-5.5 Pro or Qwen3.6-35B-A3B?
GPT-5.5 Pro has the higher public score estimate, 63.07 versus 48.34, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, GPT-5.5 Pro or Qwen3.6-35B-A3B?
GPT-5.5 Pro is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, GPT-5.5 Pro or Qwen3.6-35B-A3B?
GPT-5.5 Pro scores higher for agentic tasks on the public lane, 60.6 to 44.4. GPT-5.5 Pro and Qwen3.6-35B-A3B are 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, GPT-5.5 Pro or Qwen3.6-35B-A3B?
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, GPT-5.5 Pro or Qwen3.6-35B-A3B?
GPT-5.5 Pro has the larger documented context window: 1.05M, compared with 262K.
Related comparisons
Last updated September 4, 2026
Watch GPT-5.5 Pro vs Qwen3.6-35B-A3B
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 2,000+ readers.