| Signal | Llama 3 70B Instruct | Delta | Mistral Small 3.1 24B |
|---|---|---|---|
Capabilities | 33 | -- | |
Pricing | 1 | +0 | |
Context window size | 62 | -19 | |
Recency | 6 | -61 | |
Output Capacity | 65 | +45 | |
| Overall Result | 2 wins | of 5 | 2 wins |
0
days ranked higher
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Meta
Mistral AI
Mistral Small 3.1 24B saves you $25.00/month
That's $300.00/year compared to Llama 3 70B Instruct at your current usage level of 100K calls/month.
| Metric | Llama 3 70B Instruct | Mistral Small 3.1 24B | Winner |
|---|---|---|---|
| Overall Score | 38 | 48 | Mistral Small 3.1 24B |
| Rank | #281 | #257 | Mistral Small 3.1 24B |
| Quality Rank | #281 | #257 | Mistral Small 3.1 24B |
| Adoption Rank | #281 | #257 | Mistral Small 3.1 24B |
| Parameters | 70B | 24B | -- |
| Context Window | 8K | 128K | Mistral Small 3.1 24B |
| Pricing | $0.51/$0.74/M | $0.35/$0.56/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 33 | Llama 3 70B Instruct |
| Pricing | 1 | 1 | Llama 3 70B Instruct |
| Context window size | 62 | 81 | Mistral Small 3.1 24B |
| Recency | 6 | 67 | Mistral Small 3.1 24B |
| Output Capacity | 65 | 20 | Llama 3 70B Instruct |
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 38/100 (rank #281), placing it in the top 3% of all 290 models tracked.
Scores 48/100 (rank #257), placing it in the top 12% 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 27% better value per quality point. At 1M tokens/day, you'd spend $13.65/month with Mistral Small 3.1 24B vs $18.75/month with Llama 3 70B Instruct — a $5.10 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 (128K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.56/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (48/100) 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 9.200000000000003-point lead in composite score. It wins on more signal dimensions, but Llama 3 70B Instruct has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Llama 3 70B Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Small 3.1 24B
27% lower pricing; better value at scale
Best for Reliability
Llama 3 70B Instruct
Higher uptime and faster response speeds
Best for Prototyping
Llama 3 70B Instruct
Stronger community support and better developer experience
Best for Production
Llama 3 70B Instruct
Wider enterprise adoption and proven at scale
by Meta
by Mistral AI
| Capability | Llama 3 70B Instruct | Mistral Small 3.1 24B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Meta
Mistral AI
Mistral Small 3.1 24B saves you $0.5040/month
That's 28% cheaper than Llama 3 70B 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 | Llama 3 70B Instruct | Mistral Small 3.1 24B |
|---|---|---|
| Context Window | 8K | 128K |
| Max Output Tokens | 8,000 | -- |
| Open Source | Yes | Yes |
| Created | Apr 18, 2024 | Mar 17, 2025 |
Mistral Small 3.1 24B scores 48/100 (rank #257) compared to Llama 3 70B Instruct's 38/100 (rank #281), giving it a 9-point advantage. Mistral Small 3.1 24B is the stronger overall choice, though Llama 3 70B Instruct may excel in specific areas like certain benchmarks.
Llama 3 70B Instruct is ranked #281 and Mistral Small 3.1 24B is ranked #257 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 $0.56/M output tokens vs Llama 3 70B Instruct's $0.74/M output tokens — 1.3x more expensive. Input token pricing: Llama 3 70B Instruct at $0.51/M vs Mistral Small 3.1 24B at $0.35/M.
Mistral Small 3.1 24B has a larger context window of 128,000 tokens compared to Llama 3 70B Instruct's 8,192 tokens. A larger context window means the model can process longer documents and conversations.