| Signal | Ministral 3 14B 2512 | Delta | Qwen3 VL 235B A22B Instruct |
|---|---|---|---|
Capabilities | 67 | -- | |
Pricing | 0 | -1 | |
Context window size | 86 | -- | |
Recency | 100 | -- | |
Output Capacity | 20 | -- | |
Benchmarks | 0 | -69 | |
| Overall Result | 0 wins | of 6 | 2 wins |
7
days ranked higher
1
days
22
days ranked higher
Mistral AI
Alibaba
Ministral 3 14B 2512 saves you $34.00/month
That's $408.00/year compared to Qwen3 VL 235B A22B Instruct at your current usage level of 100K calls/month.
| Metric | Ministral 3 14B 2512 | Qwen3 VL 235B A22B Instruct | Winner |
|---|---|---|---|
| Overall Score | 74 | 74 | Qwen3 VL 235B A22B Instruct |
| Rank | #122 | #114 | Qwen3 VL 235B A22B Instruct |
| Quality Rank | #122 | #114 | Qwen3 VL 235B A22B Instruct |
| Adoption Rank | #122 | #114 | Qwen3 VL 235B A22B Instruct |
| Parameters | 14B | 235B | -- |
| Context Window | 262K | 262K | -- |
| Pricing | $0.20/$0.20/M | $0.20/$0.88/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | Ministral 3 14B 2512 |
| Pricing | 0 | 1 | Qwen3 VL 235B A22B Instruct |
| Context window size | 86 | 86 | Ministral 3 14B 2512 |
| Recency | 100 | 100 | Ministral 3 14B 2512 |
| Output Capacity | 20 | 20 | Ministral 3 14B 2512 |
| Benchmarks | -- | 69 | Qwen3 VL 235B A22B Instruct |
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 74/100 (rank #122), placing it in the top 58% of all 290 models tracked.
Scores 74/100 (rank #114), placing it in the top 61% 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.
Ministral 3 14B 2512 offers 63% better value per quality point. At 1M tokens/day, you'd spend $6.00/month with Ministral 3 14B 2512 vs $16.20/month with Qwen3 VL 235B A22B Instruct - a $10.20 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. Ministral 3 14B 2512 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 ($0.20/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (74/100) 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
Ministral 3 14B 2512 and Qwen3 VL 235B A22B Instruct are extremely close in overall performance (only 0.5 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Ministral 3 14B 2512
Marginally better benchmark scores; both are excellent
Best for Cost
Ministral 3 14B 2512
63% lower pricing; better value at scale
Best for Reliability
Ministral 3 14B 2512
Higher uptime and faster response speeds
Best for Prototyping
Ministral 3 14B 2512
Stronger community support and better developer experience
Best for Production
Ministral 3 14B 2512
Wider enterprise adoption and proven at scale
by Mistral AI
| Capability | Ministral 3 14B 2512 | Qwen3 VL 235B A22B Instruct |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Mistral AI
Alibaba
Ministral 3 14B 2512 saves you $0.8160/month
That's 58% cheaper than Qwen3 VL 235B A22B Instruct 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 | Ministral 3 14B 2512 | Qwen3 VL 235B A22B Instruct |
|---|---|---|
| Context Window | 262K | 262K |
| Max Output Tokens | -- | -- |
| Open Source | Yes | Yes |
| Created | Dec 2, 2025 | Sep 23, 2025 |
Qwen3 VL 235B A22B Instruct scores 74/100 (rank #114) compared to Ministral 3 14B 2512's 74/100 (rank #122), giving it a 1-point advantage. Qwen3 VL 235B A22B Instruct is the stronger overall choice, though Ministral 3 14B 2512 may excel in specific areas like cost efficiency.
Ministral 3 14B 2512 is ranked #122 and Qwen3 VL 235B A22B Instruct is ranked #114 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.
Ministral 3 14B 2512 is cheaper at $0.20/M output tokens vs Qwen3 VL 235B A22B Instruct's $0.88/M output tokens - 4.4x more expensive. Input token pricing: Ministral 3 14B 2512 at $0.20/M vs Qwen3 VL 235B A22B Instruct at $0.20/M.
Ministral 3 14B 2512 has a larger context window of 262,144 tokens compared to Qwen3 VL 235B A22B Instruct's 262,144 tokens. A larger context window means the model can process longer documents and conversations.