| 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 | -- | |
| Overall Result | 0 wins | of 5 | 1 wins |
6
days ranked higher
7
days
17
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 | 70 | 70 | -- |
| Rank | #121 | #124 | Ministral 3 14B 2512 |
| Quality Rank | #121 | #124 | Ministral 3 14B 2512 |
| Adoption Rank | #121 | #124 | Ministral 3 14B 2512 |
| 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 |
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 70/100 (rank #121), placing it in the top 59% of all 290 models tracked.
Scores 70/100 (rank #124), placing it in the top 58% 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.
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 (70/100) 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 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 |
Both Ministral 3 14B 2512 and Qwen3 VL 235B A22B Instruct score 70/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Ministral 3 14B 2512 is ranked #121 and Qwen3 VL 235B A22B Instruct is ranked #124 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.