Command R7B (12-2024) vs Mistral Nemo
Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 0
- Command R7B (12-2024) only
- 0
- Mistral Nemo only
- 3
- Like-for-like categories
- 0 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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
Mistral Nemo
Mistral Nemo takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Command R7B (12-2024)
Command R7B (12-2024) $0.0001, Mistral Nemo $0.0002 per turn.
List prices
At a glance
- Coding index
- Command R7B (12-2024) not benchmarked, Mistral Nemo not benchmarked.
- Widest category
- No category has a result for both models.
- Widest single gap
- No benchmark has a result for both models.
- Output price
- Both cost $0.15 per million output tokens.
- Context window
- Command R7B (12-2024) takes 128K tokens, Mistral Nemo 131K.
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.
CodingNot comparableSix of these boards feed the Vibe Coding Index0 boards, none shared
| Benchmark | Command R7B (12-2024) | Mistral Nemo | Leader |
|---|---|---|---|
| Neither model has a result on 38 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Command R7B (12-2024) | Mistral Nemo | Leader |
|---|---|---|---|
| Epoch Capabilities Index | Not measured | 118.7 | Only Mistral Nemo measured |
| Neither model has a result on the other 1 board here | |||
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command R7B (12-2024) | Mistral Nemo | Leader |
|---|---|---|---|
| Neither model has a result on 39 boards here | |||
ReasoningNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command R7B (12-2024) | Mistral Nemo | Leader |
|---|---|---|---|
| Neither model has a result on 21 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command R7B (12-2024) | Mistral Nemo | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Command R7B (12-2024) | Mistral Nemo | Leader |
|---|---|---|---|
| MMLU | Not measured | 65.3% | Only Mistral Nemo measured |
| Neither model has a result on the other 16 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command R7B (12-2024) | Mistral Nemo | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Command R7B (12-2024) | Mistral Nemo | Leader |
|---|---|---|---|
| DTBench | Not measured | 48.6% | Only Mistral Nemo measured |
| Neither model has a result on the other 45 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Command R7B (12-2024) | Mistral Nemo | 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
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) | Mistral Nemo |
|---|---|---|
| Maker | Cohere | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | December 14, 2024 | July 19, 2024 |
| Context window | 128K | 131K |
| Input $/Mtok | $0.0375 | $0.15 |
| Output $/Mtok | $0.15 | $0.15 |
| 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 Mistral Nemo 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, Command R7B (12-2024) or Mistral Nemo?
Command R7B (12-2024) costs $0.0375 per million input tokens and $0.15 per million output tokens; Mistral Nemo costs $0.15 and $0.15. Cost per solved task is known for neither of them.
Which has the bigger context window, Command R7B (12-2024) or Mistral Nemo?
Mistral Nemo, with 131K tokens against 128K.
How many benchmarks is the Command R7B (12-2024) vs Mistral Nemo comparison based on?
0 benchmarks have a result for both models as of October 21, 2026. Command R7B (12-2024)'s coding index rests on 0 independent benchmarks and Mistral Nemo's on 0. Where only one model has a result, the page says so instead of naming a winner.