o3 Pro vs Qwen2.5 7B Instruct
Qwen2.5 7B Instruct costs 400.0x less per output token than o3 Pro ($0.20 vs $80.00 per million). Updated October 21, 2026; 3 benchmarks have a result for both.
o3 Pro or Qwen2.5 7B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick o3 Pro for a larger context window (200K against 33K tokens).
- Shared results
- 3
- o3 Pro only
- 9
- Qwen2.5 7B Instruct 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
Intelligence
AA Intelligence Index
No call
Only o3 Pro has a AA Intelligence Index result, 21.9.
Directional only
Long documents
Listed context window
o3 Pro
o3 Pro takes 200K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 7B Instruct
o3 Pro $0.060, Qwen2.5 7B Instruct $0.0002 per turn.
List prices
At a glance
- Coding index
- o3 Pro not benchmarked, Qwen2.5 7B Instruct not benchmarked.
- Widest category
- Intelligence, 36.0 points apart on average over 1 shared benchmark.
- Widest single gap
- DTBench: o3 Pro 86.9% against Qwen2.5 7B Instruct 47.7%, 39.2 points apart on a 0 to 100 scale.
- Output price
- o3 Pro $80.00 against Qwen2.5 7B Instruct $0.20 per million output tokens, 400.0x apart.
- Context window
- o3 Pro takes 200K tokens, Qwen2.5 7B Instruct 33K.
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 | Qwen2.5 7B Instruct | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 3 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards, none shared
| Benchmark | o3 Pro | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | 84.9% | Not measured | Only o3 Pro measured |
| WeirdML | 58.2% | Not measured | Only o3 Pro measured |
| Neither model has a result on the other 37 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | o3 Pro | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 21.9 | Not measured | Only o3 Pro measured |
| Epoch Capabilities Index | 147.3 | 118.5 | o3 Pro |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | o3 Pro | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| BALROG | Not measured | 7.8% | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | o3 Pro | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.5% | Not measured | Only o3 Pro measured |
| GPQA Diamond (Epoch AI run) | Not measured | 35.5% | Only Qwen2.5 7B Instruct 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 | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | o3 Pro | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 2.5% | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | o3 Pro | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| MMLU | Not measured | 72.9% | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 17 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | o3 Pro | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | o3 Pro | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| DTBench | 86.9% | 47.7% | o3 Pro |
| LMCA | 38.5% | 6.4% | o3 Pro |
| 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 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | o3 Pro | Qwen2.5 7B Instruct | 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
Qwen2.5 7B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 7B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 7B Instruct 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 | Qwen2.5 7B Instruct |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | June 10, 2025 | October 16, 2024 |
| Context window | 200K | 33K |
| Input $/Mtok | $20.00 | $0.10 |
| Output $/Mtok | $80.00 | $0.20 |
| 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 Qwen2.5 7B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick o3 Pro for a larger context window (200K against 33K tokens).
Which is cheaper, o3 Pro or Qwen2.5 7B Instruct?
o3 Pro costs $20.00 per million input tokens and $80.00 per million output tokens; Qwen2.5 7B Instruct costs $0.10 and $0.20. Cost per solved task is known for neither of them.
Which has the bigger context window, o3 Pro or Qwen2.5 7B Instruct?
o3 Pro, with 200K tokens against 33K.
How many benchmarks is the o3 Pro vs Qwen2.5 7B Instruct comparison based on?
3 benchmarks have a result for both models as of October 21, 2026. o3 Pro's coding index rests on 0 independent benchmarks and Qwen2.5 7B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.