GPT Audio vs o1-pro
Updated October 21, 2026. No benchmark has tested both models yet. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
- Coding
- No data
- Overall
- No data
- Output $/M
- $10.00
- Coding
- No data
- Overall
- 12.4
- Output $/M
- $600.00
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
GPT Audio has the edge where output tokens cost 60.0x less.
No benchmark has tested both yet. GPT Audio has none yet; o1-pro on AA Intelligence Index and ARC-AGI. 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 o1-pro has a AA Intelligence Index result, 12.4.
Directional only
Long documents
Listed context window
o1-pro
o1-pro takes 200K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT Audio
GPT Audio $0.0075, o1-pro $0.450 per turn.
List prices
At a glance
- Coding index
- GPT Audio not benchmarked, o1-pro 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 Audio $10.00 against o1-pro $600.00 per million output tokens, 60.0x apart.
- Context window
- GPT Audio takes 128K tokens, o1-pro 200K.
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 Audio | o1-pro | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 12.4 | Only o1-pro measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT Audio | o1-pro | Leader |
|---|---|---|---|
| ARC-AGI | Not measured | 23.3% | Only o1-pro measured |
| Neither model has a result on the other 20 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
GPT Audio costs less
Repository review
50K input + 3K output tokens
GPT Audio costs less
Agent loop
200K input + 10K output tokens
GPT Audio 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 Audio | OpenAI o1-pro |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | January 19, 2026 | March 19, 2025 |
| Context window | 128K | 200K |
| Input $/Mtok | $2.50 | $150.00 |
| Output $/Mtok | $10.00 | $600.00 |
| 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 Audio better than o1-pro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. GPT Audio has the edge where output tokens cost 60.0x less.
Which is cheaper, GPT Audio or o1-pro?
GPT Audio costs $2.50 per million input tokens and $10.00 per million output tokens; o1-pro costs $150.00 and $600.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT Audio or o1-pro?
o1-pro, with 200K tokens against 128K.
Has any benchmark tested both GPT Audio and o1-pro?
No benchmark has tested both yet. GPT Audio has none yet; o1-pro on AA Intelligence Index and ARC-AGI. Compare them on price and context instead. Data as of October 21, 2026.