Command R7B (12-2024) vs GPT Audio
Command R7B (12-2024) costs 66.7x less per output token than GPT Audio ($0.15 vs $10.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
- Coding
- No data
- Overall
- No data
- Output $/M
- $10.00
Command R7B (12-2024) or GPT Audio: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Command R7B (12-2024) for output tokens 66.7x cheaper ($0.15 vs $10.00 per million).
No benchmark has tested either model yet, so price and context are the only way to compare them.
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
No call
Both take 128K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Command R7B (12-2024)
Command R7B (12-2024) $0.0001, GPT Audio $0.0075 per turn.
List prices
At a glance
- Coding index
- Command R7B (12-2024) not benchmarked, GPT Audio 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
- Command R7B (12-2024) $0.15 against GPT Audio $10.00 per million output tokens, 66.7x apart.
- Context window
- Both take 128K tokens.
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.
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
Command R7B (12-2024) costs less
Repository review
50K input + 3K output tokens
Command R7B (12-2024) costs less
Agent loop
200K input + 10K output tokens
Command R7B (12-2024) 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 | Cohere Command R7B (12-2024) | OpenAI GPT Audio |
|---|---|---|
| Maker | Cohere | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | December 14, 2024 | January 19, 2026 |
| Context window | 128K | 128K |
| Input $/Mtok | $0.0375 | $2.50 |
| Output $/Mtok | $0.15 | $10.00 |
| 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 Command R7B (12-2024) better than GPT Audio for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Command R7B (12-2024) for output tokens 66.7x cheaper ($0.15 vs $10.00 per million).
Which is cheaper, Command R7B (12-2024) or GPT Audio?
Command R7B (12-2024) costs $0.0375 per million input tokens and $0.15 per million output tokens; GPT Audio costs $2.50 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Command R7B (12-2024) or GPT Audio?
Neither: both take 128K tokens.
Has any benchmark tested both Command R7B (12-2024) and GPT Audio?
No benchmark has tested either model yet, so price and context are the only way to compare them. Data as of October 21, 2026.