| Signal | Command R (08-2024) | Delta | Mistral Nemo |
|---|---|---|---|
Capabilities | 50 | -- | |
Benchmarks | 47 | +47 | |
Pricing | 1 | +1 | |
Context window size | 81 | 0 | |
Recency | 29 | +8 | |
Output Capacity | 60 | -10 | |
| Overall Result | 3 wins | of 6 | 2 wins |
3
days ranked higher
1
days
26
days ranked higher
Cohere
Mistral AI
Mistral Nemo saves you $41.00/month
That's $492.00/year compared to Command R (08-2024) at your current usage level of 100K calls/month.
| Metric | Command R (08-2024) | Mistral Nemo | Winner |
|---|---|---|---|
| Overall Score | 48 | 51 | Mistral Nemo |
| Rank | #264 | #261 | Mistral Nemo |
| Quality Rank | #264 | #261 | Mistral Nemo |
| Adoption Rank | #264 | #261 | Mistral Nemo |
| Parameters | -- | -- | -- |
| Context Window | 128K | 131K | Mistral Nemo |
| Pricing | $0.15/$0.60/M | $0.02/$0.04/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | Command R (08-2024) |
| Benchmarks | 47 | -- | Command R (08-2024) |
| Pricing | 1 | 0 | Command R (08-2024) |
| Context window size | 81 | 81 | Mistral Nemo |
| Recency | 29 | 21 | Command R (08-2024) |
| Output Capacity | 60 | 70 | Mistral Nemo |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 48/100 (rank #264), placing it in the top 9% of all 290 models tracked.
Scores 51/100 (rank #261), placing it in the top 10% of all 290 models tracked.
With only a 3-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Mistral Nemo offers 92% better value per quality point. At 1M tokens/day, you'd spend $0.90/month with Mistral Nemo vs $11.25/month with Command R (08-2024) - a $10.35 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Mistral Nemo also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.04/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (51/100) correlates with better nuance, coherence, and style in long-form content
Command R (08-2024) and Mistral Nemo are extremely close in overall performance (only 3 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Command R (08-2024)
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Nemo
92% lower pricing; better value at scale
Best for Reliability
Command R (08-2024)
Higher uptime and faster response speeds
Best for Prototyping
Command R (08-2024)
Stronger community support and better developer experience
Best for Production
Command R (08-2024)
Wider enterprise adoption and proven at scale
by Cohere
| Capability | Command R (08-2024) | Mistral Nemo |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Cohere
Mistral AI
Mistral Nemo saves you $0.9060/month
That's 92% cheaper than Command R (08-2024) at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Command R (08-2024) | Mistral Nemo |
|---|---|---|
| Context Window | 128K | 131K |
| Max Output Tokens | 4,000 | 16,384 |
| Open Source | No | Yes |
| Created | Aug 30, 2024 | Jul 19, 2024 |
Mistral Nemo scores 51/100 (rank #261) compared to Command R (08-2024)'s 48/100 (rank #264), giving it a 3-point advantage. Mistral Nemo is the stronger overall choice, though Command R (08-2024) may excel in specific areas like certain benchmarks.
Command R (08-2024) is ranked #264 and Mistral Nemo is ranked #261 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Mistral Nemo is cheaper at $0.04/M output tokens vs Command R (08-2024)'s $0.60/M output tokens - 15.0x more expensive. Input token pricing: Command R (08-2024) at $0.15/M vs Mistral Nemo at $0.02/M.
Mistral Nemo has a larger context window of 131,072 tokens compared to Command R (08-2024)'s 128,000 tokens. A larger context window means the model can process longer documents and conversations.