GPT-5.2 Pro vs Qwen3.8 Omni Flash
Qwen3.8 Omni Flash costs 357.4x less per output token than GPT-5.2 Pro ($0.47 vs $168.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $168.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.47
GPT-5.2 Pro or Qwen3.8 Omni 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.
No benchmark has tested both yet. GPT-5.2 Pro has results on Epoch Capabilities Index, ARC-AGI and ARC-AGI-2; Qwen3.8 Omni Flash has none yet. 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
Long documents
Listed context window
Qwen3.8 Omni Flash
Qwen3.8 Omni Flash takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.8 Omni Flash
GPT-5.2 Pro $0.105, Qwen3.8 Omni Flash $0.0004 per turn.
List prices
At a glance
- Coding index
- GPT-5.2 Pro not benchmarked, Qwen3.8 Omni Flash 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-5.2 Pro $168.00 against Qwen3.8 Omni Flash $0.47 per million output tokens, 357.4x apart.
- Context window
- GPT-5.2 Pro takes 400K tokens, Qwen3.8 Omni Flash 1M.
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.
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5.2 Pro | Qwen3.8 Omni Flash | Leader |
|---|---|---|---|
| Epoch Capabilities Index | 156.3 | Not measured | Only GPT-5.2 Pro measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | GPT-5.2 Pro | Qwen3.8 Omni Flash | Leader |
|---|---|---|---|
| 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 |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5.2 Pro | Qwen3.8 Omni Flash | Leader |
|---|---|---|---|
| FrontierMath, tiers 1 to 3 | 74.0% | Not measured | Only GPT-5.2 Pro measured |
| FrontierMath, tier 4 | 46.0% | Not measured | Only GPT-5.2 Pro measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-5.2 Pro | Qwen3.8 Omni Flash | Leader |
|---|---|---|---|
| PRBench Finance | 46.3% | Not measured | Only GPT-5.2 Pro measured |
| PRBench Legal | 45.4% | Not measured | Only GPT-5.2 Pro measured |
| Neither model has a result on the other 18 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
Qwen3.8 Omni Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.8 Omni Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.8 Omni 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 | Qwen3.8 Omni Flash |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | December 10, 2025 | September 21, 2026 |
| Context window | 400K | 1M |
| Input $/Mtok | $21.00 | $0.15 |
| Output $/Mtok | $168.00 | $0.47 |
| 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 Qwen3.8 Omni 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 Qwen3.8 Omni Flash?
GPT-5.2 Pro costs $21.00 per million input tokens and $168.00 per million output tokens; Qwen3.8 Omni Flash costs $0.15 and $0.47. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5.2 Pro or Qwen3.8 Omni Flash?
Qwen3.8 Omni Flash, with 1M tokens against 400K.
Has any benchmark tested both GPT-5.2 Pro and Qwen3.8 Omni Flash?
No benchmark has tested both yet. GPT-5.2 Pro has results on Epoch Capabilities Index, ARC-AGI and ARC-AGI-2; Qwen3.8 Omni Flash has none yet. Compare them on price and context instead. Data as of October 22, 2026.