GPT-5 Image vs Qwen3.6 35B A3B
Qwen3.6 35B A3B costs 10.0x less per output token than GPT-5 Image ($1.00 vs $10.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $10.00
- Coding
- No data
- Overall
- 45.0
- Output $/M
- $1.00
GPT-5 Image or Qwen3.6 35B A3B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5 Image for a larger context window (400K against 262K tokens).
No benchmark has tested both yet. GPT-5 Image has results on Design Arena: images, Design Arena: graphic design and Design Arena: logos; Qwen3.6 35B A3B on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run). Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen3.6 35B A3B has a AA Intelligence Index result, 18.2.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.6 35B A3B has a AA Agentic Index result, 13.1.
Directional only
Image generation
Design Arena: images
No call
Only GPT-5 Image has a Design Arena: images result, 1191.
Directional only
Long documents
Listed context window
GPT-5 Image
GPT-5 Image takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.6 35B A3B
GPT-5 Image $0.015, Qwen3.6 35B A3B $0.0006 per turn.
List prices
At a glance
- Coding index
- GPT-5 Image not benchmarked, Qwen3.6 35B A3B not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-5 Image $10.00 against Qwen3.6 35B A3B $1.00 per million output tokens, 10.0x apart.
- Context window
- GPT-5 Image takes 400K tokens, Qwen3.6 35B A3B 262K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards measured
| Benchmark | GPT-5 Image | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 41.9 | Only Qwen3.6 35B A3B measured |
| SciCode | Not measured | 36.6% | Only Qwen3.6 35B A3B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 34.8% | Only Qwen3.6 35B A3B measured |
| Terminal-Bench | Not measured | 24.6% | Only Qwen3.6 35B A3B measured |
| WeirdML | Not measured | 34.5% | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5 Image | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 18.2 | Only Qwen3.6 35B A3B measured |
| Epoch Capabilities Index | Not measured | 143.7 | Only Qwen3.6 35B A3B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5 Image | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 13.1 | Only Qwen3.6 35B A3B measured |
| τ²-Bench Telecom | Not measured | 95.3% | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | GPT-5 Image | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 84.1% | Only Qwen3.6 35B A3B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 22.2% | Only Qwen3.6 35B A3B measured |
| GPQA Diamond (Epoch AI run) | Not measured | 84.8% | Only Qwen3.6 35B A3B measured |
| Mystery game puzzles | Not measured | 22.0% | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5 Image | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 86.7% | Only Qwen3.6 35B A3B measured |
| FrontierMath, tiers 1 to 3 | Not measured | 20.4% | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 11 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GPT-5 Image | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| IFBench | Not measured | 64.4% | Only Qwen3.6 35B A3B measured |
| Long context reasoning (AA-LCR) | Not measured | 71.7% | Only Qwen3.6 35B A3B measured |
| DTBench | Not measured | 73.9% | Only Qwen3.6 35B A3B measured |
| LMCA | Not measured | 29.7% | Only Qwen3.6 35B A3B measured |
| Surface Evolver Bench | Not measured | 44.4% | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 41 boards here | |||
Image generationDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GPT-5 Image | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| Design Arena: images | 1191 | Not measured | Only GPT-5 Image measured |
| Design Arena: graphic design | 1172 | Not measured | Only GPT-5 Image measured |
| Design Arena: logos | 1202 | Not measured | Only GPT-5 Image measured |
| Neither model has a result on the other 2 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Qwen3.6 35B A3B costs less
Repository review
50K input + 3K output tokens
Qwen3.6 35B A3B costs less
Agent loop
200K input + 10K output tokens
Qwen3.6 35B A3B costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-5 Image | Qwen3.6 35B A3B |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | October 14, 2025 | April 27, 2026 |
| Context window | 400K | 262K |
| Input $/Mtok | $10.00 | $0.10 |
| Output $/Mtok | $10.00 | $1.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Image better than Qwen3.6 35B A3B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5 Image for a larger context window (400K against 262K tokens).
Which is cheaper, GPT-5 Image or Qwen3.6 35B A3B?
GPT-5 Image costs $10.00 per million input tokens and $10.00 per million output tokens; Qwen3.6 35B A3B costs $0.10 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5 Image or Qwen3.6 35B A3B?
GPT-5 Image, with 400K tokens against 262K.
Has any benchmark tested both GPT-5 Image and Qwen3.6 35B A3B?
No benchmark has tested both yet. GPT-5 Image has results on Design Arena: images, Design Arena: graphic design and Design Arena: logos; Qwen3.6 35B A3B on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run). Compare them on price and context instead. Data as of October 22, 2026.