| Signal | Mistral Small 3.2 24B | Delta | Phi 4 |
|---|---|---|---|
Capabilities | 67 | +33 | |
Pricing | 0 | +0 | |
Context window size | 81 | +14 | |
Recency | 84 | +29 | |
Output Capacity | 85 | +15 | |
Benchmarks | 0 | -32 | |
| Overall Result | 5 wins | of 6 | 1 wins |
30
days ranked higher
0
days
0
days ranked higher
Mistral AI
Microsoft
Phi 4 saves you $2.00/month
That's $24.00/year compared to Mistral Small 3.2 24B at your current usage level of 100K calls/month.
| Metric | Mistral Small 3.2 24B | Phi 4 | Winner |
|---|---|---|---|
| Overall Score | 76 | 46 | Mistral Small 3.2 24B |
| Rank | #90 | #261 | Mistral Small 3.2 24B |
| Quality Rank | #90 | #261 | Mistral Small 3.2 24B |
| Adoption Rank | #90 | #261 | Mistral Small 3.2 24B |
| Parameters | 24B | -- | -- |
| Context Window | 131K | 16K | Mistral Small 3.2 24B |
| Pricing | $0.06/$0.18/M | $0.06/$0.14/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 33 | Mistral Small 3.2 24B |
| Pricing | 0 | 0 | Mistral Small 3.2 24B |
| Context window size | 81 | 67 | Mistral Small 3.2 24B |
| Recency | 84 | 55 | Mistral Small 3.2 24B |
| Output Capacity | 85 | 70 | Mistral Small 3.2 24B |
| Benchmarks | -- | 32 | Phi 4 |
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 76/100 (rank #90), placing it in the top 69% of all 290 models tracked.
Scores 46/100 (rank #261), placing it in the top 10% of all 290 models tracked.
Mistral Small 3.2 24B has a 30-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Mistral Small 3.2 24B offers 17% better value per quality point. At 1M tokens/day, you'd spend $3.00/month with Phi 4 vs $3.60/month with Mistral Small 3.2 24B — a $0.60 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. Phi 4 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 ($0.14/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (76/100) 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 3.2 24B clearly outperforms Phi 4 with a significant 29.9-point lead. For most general use cases, Mistral Small 3.2 24B is the stronger choice. However, Phi 4 may still excel in niche scenarios.
Best for Quality
Mistral Small 3.2 24B
Marginally better benchmark scores; both are excellent
Best for Cost
Phi 4
17% lower pricing; better value at scale
Best for Reliability
Mistral Small 3.2 24B
Higher uptime and faster response speeds
Best for Prototyping
Mistral Small 3.2 24B
Stronger community support and better developer experience
Best for Production
Mistral Small 3.2 24B
Wider enterprise adoption and proven at scale
by Mistral AI
| Capability | Mistral Small 3.2 24B | Phi 4 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Mistral AI
Microsoft
Phi 4 saves you $0.0480/month
That's 15% 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 | Mistral Small 3.2 24B | Phi 4 |
|---|---|---|
| Context Window | 131K | 16K |
| Max Output Tokens | 131,072 | 16,384 |
| Open Source | Yes | Yes |
| Created | Jun 20, 2025 | Jan 10, 2025 |
Mistral Small 3.2 24B scores 76/100 (rank #90) compared to Phi 4's 46/100 (rank #261), giving it a 30-point advantage. Mistral Small 3.2 24B is the stronger overall choice, though Phi 4 may excel in specific areas like cost efficiency.
Mistral Small 3.2 24B is ranked #90 and Phi 4 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.
Phi 4 is cheaper at $0.14/M output tokens vs Mistral Small 3.2 24B's $0.18/M output tokens — 1.3x more expensive. Input token pricing: Mistral Small 3.2 24B at $0.06/M vs Phi 4 at $0.06/M.
Mistral Small 3.2 24B has a larger context window of 131,072 tokens compared to Phi 4's 16,384 tokens. A larger context window means the model can process longer documents and conversations.