Agentic
Not comparable- GPT-5.5 Pro
- 60.6
- Estimated · #24/151
- Qwen3 235B 2507 (Reasoning)
- Not ranked
- Basis
- BenchAlign lane · 1 vs 0 public rows
- Reading
- Not comparable
GPT-5.5 Pro vs Qwen3 235B 2507 (Reasoning)
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 57.43, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
2 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 and Qwen3 235B 2507 (Reasoning) are 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
Qwen3 235B 2507 (Reasoning) is not ranked on the public lane for agentic, so no winner is named for agentic.
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
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Qwen3 235B 2507 (Reasoning) does not fit this workload in one request. GPT-5.5 Pro has no published cached-input rate, so cached tokens use its listed input rate. Qwen3 235B 2507 (Reasoning) has no comparable published API token rate.
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.
4 GPT-5.5 Pro only
2 Shared
- Shared results
- 2
- GPT-5.5 Pro only
- 4
- Qwen3 235B 2507 (Reasoning) only
- 0
- Like-for-like categories
- 0 / 8
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
Not comparable- GPT-5.5 Pro
- Not ranked
- Qwen3 235B 2507 (Reasoning)
- Not ranked
- Basis
- BenchAlign lane · 0 vs 0 public rows
- Reading
- Not comparable
Reasoning
Not comparable- GPT-5.5 Pro
- Not ranked
- Qwen3 235B 2507 (Reasoning)
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- GPT-5.5 Pro
- 61.1
- Estimated · #36/181
- Qwen3 235B 2507 (Reasoning)
- Not ranked
- Basis
- BenchAlign lane · 2 vs 0 public rows
- Reading
- Not comparable
Math
Not comparable- GPT-5.5 Pro
- 70.2
- Unranked · 3 rankable rows
- Qwen3 235B 2507 (Reasoning)
- 30.2
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 2 vs 2 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-5.5 Pro
- Not ranked
- Qwen3 235B 2507 (Reasoning)
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- GPT-5.5 Pro
- Not ranked
- Qwen3 235B 2507 (Reasoning)
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- GPT-5.5 Pro
- Not ranked
- Qwen3 235B 2507 (Reasoning)
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | GPT-5.5 Pro | Qwen3 235B 2507 (Reasoning) | Basis | Reading |
|---|---|---|---|---|
| Agentic | 60.6Estimated · #24/151 | Not ranked | Not comparableBenchAlign lane · 1 vs 0 public rows | Not comparable |
| Coding | Not ranked | Not ranked | Not comparableBenchAlign lane · 0 vs 0 public rows | Not comparable |
| Reasoning | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | 61.1Estimated · #36/181 | Not ranked | Not comparableBenchAlign lane · 2 vs 0 public rows | Not comparable |
| Math | 70.2Unranked · 3 rankable rows | 30.2Unranked · 2 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 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | 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) 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.
FrontierMath v2 (Tiers 1-3)
Math
FrontierMath v2 (Tier 4)
Math
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 235B 2507 (Reasoning)
- Self-hosted; infrastructure cost varies
- Fits in one request
Qwen3 235B 2507 (Reasoning) 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 235B 2507 (Reasoning)
- Self-hosted; infrastructure cost varies
- Fits in one request
Qwen3 235B 2507 (Reasoning) 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 235B 2507 (Reasoning)
- Self-hosted; infrastructure cost varies
- Does not fit in one request
- Cached-input rate unavailable
Qwen3 235B 2507 (Reasoning) does not fit this workload in one request. GPT-5.5 Pro has no published cached-input rate, so cached tokens use its listed input rate. Qwen3 235B 2507 (Reasoning) 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 235B 2507 (Reasoning)
Context window
Maximum documented context; output-token limits may be lower.
GPT-5.5 Pro
Qwen3 235B 2507 (Reasoning)
128K
API model ID
GPT-5.5 Pro
gpt-5.5-pro
OpenAI GPT-5.5 Pro model documentationQwen3 235B 2507 (Reasoning)
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 235B 2507 (Reasoning)
No comparable hosted API rate
Documented inputs
GPT-5.5 Pro
text, image
OpenAI model catalogQwen3 235B 2507 (Reasoning)
Not sourced
Documented outputs
GPT-5.5 Pro
Qwen3 235B 2507 (Reasoning)
Not sourced
Provider availability
GPT-5.5 Pro
Generally Available · OpenAI Responses API
OpenAI model catalogQwen3 235B 2507 (Reasoning)
Not sourced
Reasoning profile
GPT-5.5 Pro
Reasoning
Qwen3 235B 2507 (Reasoning)
Reasoning
Weight access
GPT-5.5 Pro
Proprietary
Qwen3 235B 2507 (Reasoning)
Open Weight
License
GPT-5.5 Pro
Proprietary
Qwen3 235B 2507 (Reasoning)
Open Weight
Release date
GPT-5.5 Pro
2026-04-23
Qwen3 235B 2507 (Reasoning)
2025-07-01
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 57.43, 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 evidence6 rows
Agentic
BrowseComp
GPT-5.5 Pro90.1%SourceQwen3 235B 2507 (Reasoning)—Not directly comparable
Knowledge
Math
FrontierMath (legacy)
GPT-5.5 Pro52.4%SourceQwen3 235B 2507 (Reasoning)—Not directly comparable
FrontierMath v2 (Tiers 1-3)
Shared sourceGPT-5.5 Pro51.000%Qwen3 235B 2507 (Reasoning)8.481%GPT-5.5 Pro leads this result
FrontierMath v2 (Tier 4)
Shared sourceGPT-5.5 Pro39.600%Qwen3 235B 2507 (Reasoning)0.000%GPT-5.5 Pro leads this result
Frequently asked questions
Which is better, GPT-5.5 Pro or Qwen3 235B 2507 (Reasoning)?
GPT-5.5 Pro has the higher public score estimate, 63.07 versus 57.43, 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 235B 2507 (Reasoning)?
GPT-5.5 Pro and Qwen3 235B 2507 (Reasoning) are 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 235B 2507 (Reasoning)?
Qwen3 235B 2507 (Reasoning) is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, GPT-5.5 Pro or Qwen3 235B 2507 (Reasoning)?
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 235B 2507 (Reasoning)?
GPT-5.5 Pro has the larger documented context window: 1.05M, compared with 128K.
Related comparisons
Last updated September 4, 2026
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