| Signal | Llama 3.1 Nemotron Ultra 253B v1 | Delta | Mistral Small 3.1 24B |
|---|---|---|---|
Capabilities | 50 | -- | |
Pricing | 2 | +2 | |
Context window size | 81 | -- | |
Recency | 69 | +4 | |
Output Capacity | 20 | -65 | |
| Overall Result | 2 wins | of 5 | 1 wins |
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NVIDIA
Mistral AI
Mistral Small 3.1 24B saves you $141.50/month
That's $1698.00/year compared to Llama 3.1 Nemotron Ultra 253B v1 at your current usage level of 100K calls/month.
| Metric | Llama 3.1 Nemotron Ultra 253B v1 | Mistral Small 3.1 24B | Winner |
|---|---|---|---|
| Overall Score | 58 | 66 | Mistral Small 3.1 24B |
| Rank | #233 | #176 | Mistral Small 3.1 24B |
| Quality Rank | #233 | #176 | Mistral Small 3.1 24B |
| Adoption Rank | #233 | #176 | Mistral Small 3.1 24B |
| Parameters | 253B | 24B | -- |
| Context Window | 131K | 131K | -- |
| Pricing | $0.60/$1.80/M | $0.03/$0.11/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | Llama 3.1 Nemotron Ultra 253B v1 |
| Pricing | 2 | 0 | Llama 3.1 Nemotron Ultra 253B v1 |
| Context window size | 81 | 81 | Llama 3.1 Nemotron Ultra 253B v1 |
| Recency | 69 | 65 | Llama 3.1 Nemotron Ultra 253B v1 |
| Output Capacity | 20 | 85 | Mistral Small 3.1 24B |
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 58/100 (rank #233), placing it in the top 20% of all 290 models tracked.
Scores 66/100 (rank #176), placing it in the top 40% of all 290 models tracked.
Mistral Small 3.1 24B has a 9-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Mistral Small 3.1 24B offers 94% better value per quality point. At 1M tokens/day, you'd spend $2.10/month with Mistral Small 3.1 24B vs $36.00/month with Llama 3.1 Nemotron Ultra 253B v1 - a $33.90 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 Small 3.1 24B 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 ($0.11/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (66/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Mistral Small 3.1 24B has a moderate advantage with a 8.700000000000003-point lead in composite score. It wins on more signal dimensions, but Llama 3.1 Nemotron Ultra 253B v1 has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Llama 3.1 Nemotron Ultra 253B v1
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Small 3.1 24B
94% lower pricing; better value at scale
Best for Reliability
Llama 3.1 Nemotron Ultra 253B v1
Higher uptime and faster response speeds
Best for Prototyping
Llama 3.1 Nemotron Ultra 253B v1
Stronger community support and better developer experience
Best for Production
Llama 3.1 Nemotron Ultra 253B v1
Wider enterprise adoption and proven at scale
by NVIDIA
by Mistral AI
| Capability | Llama 3.1 Nemotron Ultra 253B v1 | Mistral Small 3.1 24B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
NVIDIA
Mistral AI
Mistral Small 3.1 24B saves you $3.05/month
That's 94% cheaper than Llama 3.1 Nemotron Ultra 253B v1 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 | Llama 3.1 Nemotron Ultra 253B v1 | Mistral Small 3.1 24B |
|---|---|---|
| Context Window | 131K | 131K |
| Max Output Tokens | -- | 131,072 |
| Open Source | Yes | Yes |
| Created | Apr 8, 2025 | Mar 17, 2025 |
Mistral Small 3.1 24B scores 66/100 (rank #176) compared to Llama 3.1 Nemotron Ultra 253B v1's 58/100 (rank #233), giving it a 9-point advantage. Mistral Small 3.1 24B is the stronger overall choice, though Llama 3.1 Nemotron Ultra 253B v1 may excel in specific areas like certain benchmarks.
Llama 3.1 Nemotron Ultra 253B v1 is ranked #233 and Mistral Small 3.1 24B is ranked #176 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 Small 3.1 24B is cheaper at $0.11/M output tokens vs Llama 3.1 Nemotron Ultra 253B v1's $1.80/M output tokens - 16.4x more expensive. Input token pricing: Llama 3.1 Nemotron Ultra 253B v1 at $0.60/M vs Mistral Small 3.1 24B at $0.03/M.
Llama 3.1 Nemotron Ultra 253B v1 has a larger context window of 131,072 tokens compared to Mistral Small 3.1 24B's 131,072 tokens. A larger context window means the model can process longer documents and conversations.