o3 Pro vs Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B leads o3 Pro on the Artificial Analysis Intelligence Index, 39.9 to 21.9, and Qwen3.8 2.4T A95B costs 13.3x less per output token ($6.00 vs $80.00 per million). Updated October 22, 2026; 2 benchmarks have a result for both.
o3 Pro or Qwen3.8 2.4T A95B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick o3 Pro for work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.
- Shared results
- 2
- o3 Pro only
- 10
- Qwen3.8 2.4T A95B only
- 5
- 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
Intelligence
AA Intelligence Index
Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B leads, 39.9 against 21.9.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.8 2.4T A95B has a AA Agentic Index result, 50.1.
Directional only
Long documents
Listed context window
Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B takes 1.05M tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.8 2.4T A95B
o3 Pro $0.060, Qwen3.8 2.4T A95B $0.0050 per turn.
List prices
At a glance
- Coding index
- o3 Pro not benchmarked, Qwen3.8 2.4T A95B not benchmarked.
- Widest category
- Intelligence, 18.0 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: o3 Pro 21.9 against Qwen3.8 2.4T A95B 39.9, 18.0 points apart on a 0 to 100 scale.
- Output price
- o3 Pro $80.00 against Qwen3.8 2.4T A95B $6.00 per million output tokens, 13.3x apart.
- Context window
- o3 Pro takes 200K tokens, Qwen3.8 2.4T A95B 1.05M.
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 | o3 Pro | Bars | Qwen3.8 2.4T A95B | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| All shared boards | 0 | 2 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards, none shared
| Benchmark | o3 Pro | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| Aider polyglot | 84.9% | Not measured | Only o3 Pro measured |
| AA Coding Index | Not measured | 71.9 | Only Qwen3.8 2.4T A95B measured |
| SciCode | Not measured | 54.1% | Only Qwen3.8 2.4T A95B measured |
| WeirdML | 58.2% | Not measured | Only o3 Pro measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | o3 Pro | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| AA Intelligence Index | 21.9 | 39.9 | Qwen3.8 2.4T A95B |
| Epoch Capabilities Index | 147.3 | Not measured | Only o3 Pro measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | o3 Pro | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 50.1 | Only Qwen3.8 2.4T A95B measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | o3 Pro | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.5% | 93.5% | Qwen3.8 2.4T A95B |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 42.4% | Only Qwen3.8 2.4T A95B measured |
| ARC-AGI | 59.3% | Not measured | Only o3 Pro measured |
| ARC-AGI-2 | 4.9% | Not measured | Only o3 Pro measured |
| Kagi LLM Benchmark | 72.1% | Not measured | Only o3 Pro measured |
| Neither model has a result on the other 17 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | o3 Pro | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | o3 Pro | Qwen3.8 2.4T A95B | 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 | o3 Pro | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | o3 Pro | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 80.3% | Only Qwen3.8 2.4T A95B measured |
| DTBench | 86.9% | Not measured | Only o3 Pro measured |
| LMCA | 38.5% | Not measured | Only o3 Pro measured |
| Fiction.LiveBench | 97.2% | Not measured | Only o3 Pro measured |
| Creative writing (Lech Mazur) | 84.4% | Not measured | Only o3 Pro measured |
| Neither model has a result on the other 41 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | o3 Pro | Qwen3.8 2.4T A95B | 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
Qwen3.8 2.4T A95B costs less
Repository review
50K input + 3K output tokens
Qwen3.8 2.4T A95B costs less
Agent loop
200K input + 10K output tokens
Qwen3.8 2.4T A95B 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 o3 Pro | Qwen3.8 2.4T A95B |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | June 10, 2025 | August 12, 2026 |
| Context window | 200K | 1.05M |
| Input $/Mtok | $20.00 | $2.00 |
| Output $/Mtok | $80.00 | $6.00 |
| 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 o3 Pro better than Qwen3.8 2.4T A95B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick o3 Pro for work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.
Which is cheaper, o3 Pro or Qwen3.8 2.4T A95B?
o3 Pro costs $20.00 per million input tokens and $80.00 per million output tokens; Qwen3.8 2.4T A95B costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, o3 Pro or Qwen3.8 2.4T A95B?
Qwen3.8 2.4T A95B, with 1.05M tokens against 200K.
How many benchmarks is the o3 Pro vs Qwen3.8 2.4T A95B comparison based on?
2 benchmarks have a result for both models as of October 22, 2026. o3 Pro's coding index rests on 0 independent benchmarks and Qwen3.8 2.4T A95B's on 0. Where only one model has a result, the page says so instead of naming a winner.