| Signal | Mistral Nemo | Delta | Qwen2.5 72B Instruct |
|---|---|---|---|
Capabilities | 50 | -- | |
Pricing | 100 | +0 | |
Context window size | 73 | -- | |
Recency | 10 | -11 | |
Output Capacity | 20 | -50 | |
| Overall Result | 1 wins | of 5 | 2 wins |
Score History
40
current score
Tied
right now
40
current score
Mistral AI
Alibaba
Mistral Nemo saves you $52.50/month
That's $630.00/year compared to Qwen2.5 72B Instruct at your current usage level of 100K calls/month.
| Metric | Mistral Nemo | Qwen2.5 72B Instruct | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #299 | #298 | Qwen2.5 72B Instruct |
| Quality Rank | #299 | #298 | Qwen2.5 72B Instruct |
| Adoption Rank | #299 | #298 | Qwen2.5 72B Instruct |
| Parameters | -- | 72B | -- |
| Context Window | 131K | 131K | -- |
| Pricing | $0.02/$0.03/M | $0.36/$0.40/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | Mistral Nemo |
| Pricing | 100 | 100 | Mistral Nemo |
| Context window size | 73 | 73 | Mistral Nemo |
| Recency | 10 | 21 | Qwen2.5 72B Instruct |
| Output Capacity | 20 | 70 | Qwen2.5 72B Instruct |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 40/100 (rank #299), placing it in the top -3% of all 290 models tracked.
Scores 40/100 (rank #298), placing it in the top -2% of all 290 models tracked.
With only a 0-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 93% better value per quality point. At 1M tokens/day, you'd spend $0.75/month with Mistral Nemo vs $11.40/month with Qwen2.5 72B Instruct - a $10.65 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
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. 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 ($0.03/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content
Mistral Nemo and Qwen2.5 72B Instruct are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Mistral Nemo
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Nemo
93% lower pricing; better value at scale
Best for Reliability
Mistral Nemo
Higher uptime and faster response speeds
Best for Prototyping
Mistral Nemo
Stronger community support and better developer experience
Best for Production
Mistral Nemo
Wider enterprise adoption and proven at scale
by Mistral AI
| Capability | Mistral Nemo | Qwen2.5 72B Instruct |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Mistral AI
Alibaba
Mistral Nemo saves you $1.06/month
That's 94% cheaper than Qwen2.5 72B Instruct 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 | Mistral Nemo | Qwen2.5 72B Instruct |
|---|---|---|
| Context Window | 131K | 131K |
| Max Output Tokens | -- | 16,384 |
| Open Source | Yes | Yes |
| Created | Jul 19, 2024 | Sep 19, 2024 |