GPT-5.2 Pro vs Qwen3.7 Flash
Qwen3.7 Flash costs 1292.3x less per output token than GPT-5.2 Pro ($0.13 vs $168.00 per million). Updated October 21, 2026; 2 benchmarks have a result for both.
GPT-5.2 Pro or Qwen3.7 Flash: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 2
- GPT-5.2 Pro only
- 5
- Qwen3.7 Flash only
- 4
- Like-for-like categories
- 2 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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
Long documents
Listed context window
Qwen3.7 Flash
Qwen3.7 Flash takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.7 Flash
GPT-5.2 Pro $0.105, Qwen3.7 Flash $0.0001 per turn.
List prices
At a glance
- Coding index
- GPT-5.2 Pro not benchmarked, Qwen3.7 Flash not benchmarked.
- Widest category
- Math, 54.7 points apart on average over 1 shared benchmark.
- Widest single gap
- FrontierMath, tiers 1 to 3: GPT-5.2 Pro 74.0% against Qwen3.7 Flash 19.3%, 54.7 points apart on a 0 to 100 scale.
- Output price
- GPT-5.2 Pro $168.00 against Qwen3.7 Flash $0.13 per million output tokens, 1292.3x apart.
- Context window
- GPT-5.2 Pro takes 400K tokens, Qwen3.7 Flash 1M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-5.2 Pro | Bars | Qwen3.7 Flash | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Math | 1 | 0 | ||
| All shared boards | 2 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index1 board, none shared
| Benchmark | GPT-5.2 Pro | Qwen3.7 Flash | Leader |
|---|---|---|---|
| ALE-Bench | Not measured | 420.1 | Only Qwen3.7 Flash measured |
| Neither model has a result on the other 38 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.2 Pro | Qwen3.7 Flash | Leader |
|---|---|---|---|
| Epoch Capabilities Index | 156.3 | 144.1 | GPT-5.2 Pro |
| Neither model has a result on the other 1 board here | |||
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2 Pro | Qwen3.7 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.2 Pro | Qwen3.7 Flash | Leader |
|---|---|---|---|
| GPQA Diamond (Epoch AI run) | Not measured | 82.3% | Only Qwen3.7 Flash measured |
| ARC-AGI | 90.5% | Not measured | Only GPT-5.2 Pro measured |
| ARC-AGI-2 | 54.2% | Not measured | Only GPT-5.2 Pro measured |
| SimpleBench | 57.4% | Not measured | Only GPT-5.2 Pro measured |
| Chess puzzles | 60.0% | Not measured | Only GPT-5.2 Pro measured |
| Mystery game puzzles | Not measured | 15.0% | Only Qwen3.7 Flash measured |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.2 Pro | Qwen3.7 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 86.7% | Only Qwen3.7 Flash measured |
| FrontierMath, tiers 1 to 3 | 74.0% | 19.3% | GPT-5.2 Pro |
| FrontierMath, tier 4 | 46.0% | Not measured | Only GPT-5.2 Pro measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2 Pro | Qwen3.7 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2 Pro | Qwen3.7 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2 Pro | Qwen3.7 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 46 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2 Pro | Qwen3.7 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 5 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
Qwen3.7 Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.7 Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.7 Flash 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-5.2 Pro | Qwen3.7 Flash |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | December 10, 2025 | July 27, 2026 |
| Context window | 400K | 1M |
| Input $/Mtok | $21.00 | $0.03 |
| Output $/Mtok | $168.00 | $0.13 |
| 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-5.2 Pro better than Qwen3.7 Flash for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-5.2 Pro or Qwen3.7 Flash?
GPT-5.2 Pro costs $21.00 per million input tokens and $168.00 per million output tokens; Qwen3.7 Flash costs $0.03 and $0.13. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5.2 Pro or Qwen3.7 Flash?
Qwen3.7 Flash, with 1M tokens against 400K.
How many benchmarks is the GPT-5.2 Pro vs Qwen3.7 Flash comparison based on?
2 benchmarks have a result for both models as of October 21, 2026. GPT-5.2 Pro's coding index rests on 0 independent benchmarks and Qwen3.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.