| Signal | Gemma 3n 4B (free) | Delta | Mistral Small 3.2 24B |
|---|---|---|---|
Capabilities | 33 | -33 | |
Pricing | 30 | +30 | |
Context window size | 62 | -19 | |
Recency | 75 | -6 | |
Output Capacity | 55 | +35 | |
| Overall Result | 2 wins | of 5 | 3 wins |
9
days higher
3
days
18
days higher
Mistral AI
Gemma 3n 4B (free) saves you $17.50/month
That's $210.00/year compared to Mistral Small 3.2 24B at your current usage level of 100K calls/month.
| Metric | Gemma 3n 4B (free) | Mistral Small 3.2 24B | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #231 | #229 | Mistral Small 3.2 24B |
| Quality Rank | #231 | #229 | Mistral Small 3.2 24B |
| Adoption Rank | #231 | #229 | Mistral Small 3.2 24B |
| Parameters | 4B | 24B | -- |
| Context Window | 8K | 128K | Mistral Small 3.2 24B |
| Pricing | Free | $0.07/$0.20/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 67 | Mistral Small 3.2 24B |
| Pricing | 30 | 0 | Gemma 3n 4B (free) |
| Context window size | 62 | 81 | Mistral Small 3.2 24B |
| Recency | 75 | 81 | Mistral Small 3.2 24B |
| Output Capacity | 55 | 20 | Gemma 3n 4B (free) |
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%). Here's what the scores mean for these two models:
Scores 40/100 (rank #231), placing it in the top 21% of all 290 models tracked.
Scores 40/100 (rank #229), placing it in the top 21% 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.
Compare the cost per quality point to find the best value for your specific workload.
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. Gemma 3n 4B (free) 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 ($0.00/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
Gemma 3n 4B (free) and Mistral Small 3.2 24B 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
Gemma 3n 4B (free)
Marginally better benchmark scores; both are excellent
Best for Cost
Gemma 3n 4B (free)
100% lower pricing; better value at scale
Best for Reliability
Gemma 3n 4B (free)
Higher uptime and faster response speeds
Best for Prototyping
Gemma 3n 4B (free)
Stronger community support and better developer experience
Best for Production
Gemma 3n 4B (free)
Wider enterprise adoption and proven at scale
by Google
| Capability | Gemma 3n 4B (free) | Mistral Small 3.2 24B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Mistral AI
Gemma 3n 4B (free) saves you $0.3750/month
That's 100% cheaper than Mistral Small 3.2 24B 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 | Gemma 3n 4B (free) | Mistral Small 3.2 24B |
|---|---|---|
| Context Window | 8K | 128K |
| Max Output Tokens | 2,048 | -- |
| Open Source | Yes | Yes |
| Created | May 20, 2025 | Jun 20, 2025 |
Both Gemma 3n 4B (free) and Mistral Small 3.2 24B score 40/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Gemma 3n 4B (free) is ranked #231 and Mistral Small 3.2 24B is ranked #229 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Gemma 3n 4B (free) is cheaper at $0.00/M output tokens vs Mistral Small 3.2 24B's $0.20/M output tokens - 200.0x more expensive. Input token pricing: Gemma 3n 4B (free) at $0.00/M vs Mistral Small 3.2 24B at $0.07/M.
Mistral Small 3.2 24B has a larger context window of 128,000 tokens compared to Gemma 3n 4B (free)'s 8,192 tokens. A larger context window means the model can process longer documents and conversations.