Llama 3.2 3B Instruct vs Mistral Small 4 (batch)
| Signal | Llama 3.2 3B Instruct | Delta | Mistral Small 4 (batch) |
|---|---|---|---|
Capabilities | 33 | -50 | |
Benchmarks | 33 | +33 | |
Pricing | 100 | -- | |
Context window size | 81 | -5 | |
Recency | 0 | -98 | |
Output Capacity | 81 | -4 | |
| Overall Result | 1 wins | of 6 | 4 wins |
Score History
34.3
current score
Mistral Small 4 (batch)
right now
40
current score
Llama 3.2 3B Instruct
Meta
Mistral Small 4 (batch)
Mistral AI
Llama 3.2 3B Instruct saves you $1.00/month
That's $12.00/year compared to Mistral Small 4 (batch) at your current usage level of 100K calls/month.
| Metric | Llama 3.2 3B Instruct | Mistral Small 4 (batch) | Winner |
|---|---|---|---|
| Overall Score | 34 | 40 | Mistral Small 4 (batch) |
| Rank | #422 | #337 | Mistral Small 4 (batch) |
| Quality Rank | #422 | #337 | Mistral Small 4 (batch) |
| Adoption Rank | #422 | #337 | Mistral Small 4 (batch) |
| Parameters | 3B | -- | -- |
| Context Window | 131K | 262K | Mistral Small 4 (batch) |
| Pricing | $0.05/$0.33/M | $0.07/$0.30/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 83 | Mistral Small 4 (batch) |
| Benchmarks | 33 | -- | Llama 3.2 3B Instruct |
| Pricing | 100 | 100 | Llama 3.2 3B Instruct |
| Context window size | 81 | 86 | Mistral Small 4 (batch) |
| Recency | 0 | 98 | Mistral Small 4 (batch) |
| Output Capacity | 81 | 85 | Mistral Small 4 (batch) |
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 34/100 (rank #422), placing it in the top -45% of all 290 models tracked.
Scores 40/100 (rank #337), placing it in the top -16% of all 290 models tracked.
Mistral Small 4 (batch) has a 6-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Choose Llama 3.2 3B Instruct when you need:
- Self-hosted deployments where you need full control over the model
Choose Mistral Small 4 (batch) when you need:
- Processing long documents or large codebases (262K token context)
- Multimodal workflows that require image understanding
- Agentic applications using tool/function calling
- Step-by-step reasoning and chain-of-thought problem solving
- Self-hosted deployments where you need full control over the model
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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 Small 4 (batch) also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (262K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.30/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
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Mistral Small 4 (batch) has a moderate advantage with a 5.700000000000003-point lead in composite score. It wins on more signal dimensions, but Llama 3.2 3B Instruct has specific strengths that could make it the better choice for certain workflows.
By Use Case
Best for Quality
Llama 3.2 3B Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Small 4 (batch)
1% lower pricing; better value at scale
Best for Reliability
Llama 3.2 3B Instruct
Higher uptime and faster response speeds
Best for Prototyping
Llama 3.2 3B Instruct
Stronger community support and better developer experience
Best for Production
Llama 3.2 3B Instruct
Wider enterprise adoption and proven at scale
by Meta
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Reliability - Higher uptime and faster response speeds
- Choose for Prototyping - Stronger community support and better developer experience
- Choose for Production - Wider enterprise adoption and proven at scale
by Mistral AI
- Choose for Cost - 1% lower pricing; better value at scale
| Capability | Llama 3.2 3B Instruct | Mistral Small 4 (batch) |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Llama 3.2 3B Instruct
Meta
Mistral Small 4 (batch)
Mistral AI
Llama 3.2 3B Instruct saves you $0.009000/month
That's 2% cheaper than Mistral Small 4 (batch) 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 3.2 3B Instruct | Mistral Small 4 (batch) |
|---|---|---|
| Context Window | 131K | 262K |
| Max Output Tokens | 117,964 | 209,715 |
| Open Source | Yes | Yes |
| Created | Sep 25, 2024 | Mar 16, 2026 |