| Signal | Cogito v2.1 671B | Delta | Mistral Small 3.2 24B |
|---|---|---|---|
Capabilities | 50 | -17 | |
Pricing | 1 | +1 | |
Context window size | 81 | -- | |
Recency | 100 | +19 | |
Output Capacity | 20 | -- | |
| Overall Result | 2 wins | of 5 | 1 wins |
10
days higher
4
days
16
days higher
deepcogito
Mistral AI
Mistral Small 3.2 24B saves you $170.00/month
That's $2040.00/year compared to Cogito v2.1 671B at your current usage level of 100K calls/month.
| Metric | Cogito v2.1 671B | Mistral Small 3.2 24B | Winner |
|---|---|---|---|
| Overall Score | 67 | 67 | Mistral Small 3.2 24B |
| Rank | #183 | #181 | Mistral Small 3.2 24B |
| Quality Rank | #183 | #181 | Mistral Small 3.2 24B |
| Adoption Rank | #183 | #181 | Mistral Small 3.2 24B |
| Parameters | 671B | 24B | -- |
| Context Window | 128K | 128K | -- |
| Pricing | $1.25/$1.25/M | $0.07/$0.20/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | Mistral Small 3.2 24B |
| Pricing | 1 | 0 | Cogito v2.1 671B |
| Context window size | 81 | 81 | Cogito v2.1 671B |
| Recency | 100 | 81 | Cogito v2.1 671B |
| Output Capacity | 20 | 20 | Cogito v2.1 671B |
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 67/100 (rank #183), placing it in the top 37% of all 290 models tracked.
Scores 67/100 (rank #181), placing it in the top 38% 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.
Mistral Small 3.2 24B offers 89% better value per quality point. At 1M tokens/day, you'd spend $4.13/month with Mistral Small 3.2 24B vs $37.50/month with Cogito v2.1 671B - a $33.38 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 (128K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.20/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (67/100) 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
Cogito v2.1 671B and Mistral Small 3.2 24B are extremely close in overall performance (only 0.20000000000000284 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Cogito v2.1 671B
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Small 3.2 24B
89% lower pricing; better value at scale
Best for Reliability
Cogito v2.1 671B
Higher uptime and faster response speeds
Best for Prototyping
Cogito v2.1 671B
Stronger community support and better developer experience
Best for Production
Cogito v2.1 671B
Wider enterprise adoption and proven at scale
by deepcogito
by Mistral AI
| Capability | Cogito v2.1 671B | Mistral Small 3.2 24B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
deepcogito
Mistral AI
Mistral Small 3.2 24B saves you $3.38/month
That's 90% cheaper than Cogito v2.1 671B 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 | Cogito v2.1 671B | Mistral Small 3.2 24B |
|---|---|---|
| Context Window | 128K | 128K |
| Max Output Tokens | -- | -- |
| Open Source | No | Yes |
| Created | Nov 13, 2025 | Jun 20, 2025 |
Mistral Small 3.2 24B scores 67/100 (rank #181) compared to Cogito v2.1 671B's 67/100 (rank #183), giving it a 0-point advantage. Mistral Small 3.2 24B is the stronger overall choice, though Cogito v2.1 671B may excel in specific areas like certain benchmarks.
Cogito v2.1 671B is ranked #183 and Mistral Small 3.2 24B is ranked #181 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 $0.20/M output tokens vs Cogito v2.1 671B's $1.25/M output tokens - 6.3x more expensive. Input token pricing: Cogito v2.1 671B at $1.25/M vs Mistral Small 3.2 24B at $0.07/M.
Cogito v2.1 671B has a larger context window of 128,000 tokens compared to Mistral Small 3.2 24B's 128,000 tokens. A larger context window means the model can process longer documents and conversations.