Math
Like-for-like- GPT-4.1
- 4.1
- Qwen3.5 Plus
- 16.3
- Weighted basis
- 2 vs 2 rows
- Reading
- Qwen3.5 Plus leads
GPT-4.1 vs Qwen3.5 Plus
Updated August 13, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
GPT-4.1 has the higher public score estimate, 50.71 versus 46.73, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
2 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
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.
Chat turn cost
1K fresh input + 500 output tokens
Qwen3.5 Plus
Qwen3.5 Plus has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Qwen3.5 Plus
Qwen3.5 Plus has the lower estimated token cost for this stated workload. GPT-4.1 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.5 Plus has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Qwen3.5 Plus
Qwen3.5 Plus has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
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-4.1 only
2 Shared
2 Qwen3.5 Plus only
- Shared results
- 2
- GPT-4.1 only
- 5
- Qwen3.5 Plus only
- 2
- Like-for-like categories
- 1 / 8
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Agentic
Not comparable- GPT-4.1
- Not measured
- Qwen3.5 Plus
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Coding
Not comparable- GPT-4.1
- 54.6
- Qwen3.5 Plus
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- GPT-4.1
- Not measured
- Qwen3.5 Plus
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- GPT-4.1
- 66.3
- Qwen3.5 Plus
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-4.1
- Not measured
- Qwen3.5 Plus
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- GPT-4.1
- Not measured
- Qwen3.5 Plus
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- GPT-4.1
- 87.4
- Qwen3.5 Plus
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
| Category | GPT-4.1 | Qwen3.5 Plus | Weighted basis | Reading |
|---|---|---|---|---|
| Math | 4.1 | 16.3 | Like-for-like2 vs 2 rows | Qwen3.5 Plus leads |
| Agentic | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Coding | 54.6 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | 66.3 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | 87.4 | Not measured | Not comparable1 vs 0 rows | Not comparable |
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-4.1
- $0.006
- Fits in one request
- Qwen3.5 Plus
- $0.0016
- Fits in one request
Qwen3.5 Plus has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- GPT-4.1
- $0.124
- Fits in one request
- Qwen3.5 Plus
- $0.0272
- Fits in one request
Qwen3.5 Plus has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GPT-4.1
- $0.52
- Fits in one request
- Cached input priced at the published list-input rate
- Qwen3.5 Plus
- $0.112
- Fits in one request
- Cached input priced at the published list-input rate
Qwen3.5 Plus has the lower modeled cost
GPT-4.1 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.5 Plus has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGPT-4.1Qwen3.5 Plus
Context window
Maximum documented context; output-token limits may be lower.
GPT-4.1
1M
Qwen3.5 Plus
1M
API model ID
GPT-4.1
Not sourced
Qwen3.5 Plus
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GPT-4.1
Not published
Qwen3.5 Plus
Not published
Documented inputs
GPT-4.1
Not sourced
Qwen3.5 Plus
Not sourced
Documented outputs
GPT-4.1
Not sourced
Qwen3.5 Plus
Not sourced
Provider availability
GPT-4.1
Not sourced
Qwen3.5 Plus
Not sourced
Reasoning profile
GPT-4.1
Non-Reasoning
Qwen3.5 Plus
Reasoning
Weight access
GPT-4.1
Proprietary
Qwen3.5 Plus
Proprietary
License
GPT-4.1
Proprietary
Qwen3.5 Plus
Proprietary
Release date
GPT-4.1
2025-04-14
Qwen3.5 Plus
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
- GPT-4.1 has the higher public score estimate, 50.71 versus 46.73, but the 90% score intervals overlap.
- Workload cost
- Repository review: $0.124 vs $0.0272. Cache-heavy agent loop: $0.52 vs $0.112.
- Context tradeoff
- Both models list 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 evidence9 rows
Agentic
Coding
Knowledge
Math
FrontierMath v2 (Tiers 1-3)
Shared sourceGPT-4.15.517%Qwen3.5 Plus21.034%Qwen3.5 Plus leads this result
FrontierMath v2 (Tier 4)
Shared sourceGPT-4.10.000%Qwen3.5 Plus2.083%Qwen3.5 Plus leads this result
Instruction following
IFEval
GPT-4.187.4%SourceQwen3.5 Plus—Not directly comparable
Frequently asked questions
Which is better, GPT-4.1 or Qwen3.5 Plus?
GPT-4.1 has the higher public score estimate, 50.71 versus 46.73, 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-4.1 or Qwen3.5 Plus?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, GPT-4.1 or Qwen3.5 Plus?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, GPT-4.1 or Qwen3.5 Plus?
For the stated presets, chat costs $0.006 on GPT-4.1 and $0.0016 on Qwen3.5 Plus; repository review costs $0.124 and $0.0272; the cache-heavy agent loop costs $0.52 and $0.112. GPT-4.1 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.5 Plus has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, GPT-4.1 or Qwen3.5 Plus?
Both models list the same context window, 1M.
Related comparisons
Last updated August 13, 2026
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