| Signal | Mistral Small 3.2 24B | Delta | R1 0528 |
|---|---|---|---|
Capabilities | 67 | -- | |
Pricing | 0 | -2 | |
Context window size | 81 | -2 | |
Recency | 84 | +4 | |
Output Capacity | 85 | +5 | |
| Overall Result | 2 wins | of 5 | 2 wins |
14
days ranked higher
7
days
9
days ranked higher
Mistral AI
DeepSeek
Mistral Small 3.2 24B saves you $137.50/month
That's $1650.00/year compared to R1 0528 at your current usage level of 100K calls/month.
| Metric | Mistral Small 3.2 24B | R1 0528 | Winner |
|---|---|---|---|
| Overall Score | 76 | 75 | Mistral Small 3.2 24B |
| Rank | #90 | #93 | Mistral Small 3.2 24B |
| Quality Rank | #90 | #93 | Mistral Small 3.2 24B |
| Adoption Rank | #90 | #93 | Mistral Small 3.2 24B |
| Parameters | 24B | -- | -- |
| Context Window | 131K | 164K | R1 0528 |
| Pricing | $0.06/$0.18/M | $0.45/$2.15/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | Mistral Small 3.2 24B |
| Pricing | 0 | 2 | R1 0528 |
| Context window size | 81 | 83 | R1 0528 |
| Recency | 84 | 80 | Mistral Small 3.2 24B |
| Output Capacity | 85 | 80 | Mistral Small 3.2 24B |
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 75/100 (rank #93), placing it in the top 68% of all 290 models tracked.
With only a 1-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.
Mistral Small 3.2 24B offers 91% better value per quality point. At 1M tokens/day, you'd spend $3.60/month with Mistral Small 3.2 24B vs $39.00/month with R1 0528 — a $35.40 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 3.2 24B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (164K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.18/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 and R1 0528 are extremely close in overall performance (only 1.2999999999999972 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Mistral Small 3.2 24B
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Small 3.2 24B
91% 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 | R1 0528 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Mistral AI
DeepSeek
Mistral Small 3.2 24B saves you $3.07/month
That's 90% cheaper than R1 0528 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 | R1 0528 |
|---|---|---|
| Context Window | 131K | 164K |
| Max Output Tokens | 131,072 | 65,536 |
| Open Source | Yes | Yes |
| Created | Jun 20, 2025 | May 28, 2025 |
Mistral Small 3.2 24B scores 76/100 (rank #90) compared to R1 0528's 75/100 (rank #93), giving it a 1-point advantage. Mistral Small 3.2 24B is the stronger overall choice, though R1 0528 may excel in specific areas like certain benchmarks.
Mistral Small 3.2 24B is ranked #90 and R1 0528 is ranked #93 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 3.2 24B is cheaper at $0.18/M output tokens vs R1 0528's $2.15/M output tokens — 11.9x more expensive. Input token pricing: Mistral Small 3.2 24B at $0.06/M vs R1 0528 at $0.45/M.
R1 0528 has a larger context window of 163,840 tokens compared to Mistral Small 3.2 24B's 131,072 tokens. A larger context window means the model can process longer documents and conversations.