| Signal | Llama 3 70B Instruct | Delta | Mistral Nemo |
|---|---|---|---|
Capabilities | 33 | -17 | |
Benchmarks | 50 | +50 | |
Pricing | 1 | +1 | |
Context window size | 62 | -19 | |
Recency | 4 | -17 | |
Output Capacity | 65 | -5 | |
| Overall Result | 2 wins | of 6 | 4 wins |
0
days ranked higher
0
days
30
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Meta
Mistral AI
Mistral Nemo saves you $84.00/month
That's $1008.00/year compared to Llama 3 70B Instruct at your current usage level of 100K calls/month.
| Metric | Llama 3 70B Instruct | Mistral Nemo | Winner |
|---|---|---|---|
| Overall Score | 40 | 51 | Mistral Nemo |
| Rank | #282 | #261 | Mistral Nemo |
| Quality Rank | #282 | #261 | Mistral Nemo |
| Adoption Rank | #282 | #261 | Mistral Nemo |
| Parameters | 70B | -- | -- |
| Context Window | 8K | 131K | Mistral Nemo |
| Pricing | $0.51/$0.74/M | $0.02/$0.04/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 50 | Mistral Nemo |
| Benchmarks | 50 | -- | Llama 3 70B Instruct |
| Pricing | 1 | 0 | Llama 3 70B Instruct |
| Context window size | 62 | 81 | Mistral Nemo |
| Recency | 4 | 21 | Mistral Nemo |
| Output Capacity | 65 | 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 40/100 (rank #282), placing it in the top 3% of all 290 models tracked.
Scores 51/100 (rank #261), placing it in the top 10% of all 290 models tracked.
Mistral Nemo has a 10-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Mistral Nemo offers 95% better value per quality point. At 1M tokens/day, you'd spend $0.90/month with Mistral Nemo vs $18.75/month with Llama 3 70B Instruct - a $17.85 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
Mistral Nemo clearly outperforms Llama 3 70B Instruct with a significant 10.100000000000001-point lead. For most general use cases, Mistral Nemo is the stronger choice. However, Llama 3 70B Instruct may still excel in niche scenarios.
Best for Quality
Llama 3 70B Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Nemo
95% 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
| Capability | Llama 3 70B Instruct | Mistral Nemo |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Meta
Mistral AI
Mistral Nemo saves you $1.72/month
That's 95% 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 Nemo |
|---|---|---|
| Context Window | 8K | 131K |
| Max Output Tokens | 8,000 | 16,384 |
| Open Source | Yes | Yes |
| Created | Apr 18, 2024 | Jul 19, 2024 |
Mistral Nemo scores 51/100 (rank #261) compared to Llama 3 70B Instruct's 40/100 (rank #282), giving it a 10-point advantage. Mistral Nemo is the stronger overall choice, though Llama 3 70B Instruct may excel in specific areas like certain benchmarks.
Llama 3 70B Instruct is ranked #282 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 Llama 3 70B Instruct's $0.74/M output tokens - 18.5x more expensive. Input token pricing: Llama 3 70B Instruct at $0.51/M vs Mistral Nemo at $0.02/M.
Mistral Nemo has a larger context window of 131,072 tokens compared to Llama 3 70B Instruct's 8,192 tokens. A larger context window means the model can process longer documents and conversations.