| Signal | Ministral 3 14B 2512 | Delta | WizardLM-2 8x22B |
|---|---|---|---|
Capabilities | 67 | +50 | |
Pricing | 0 | 0 | |
Context window size | 86 | +10 | |
Recency | 100 | +94 | |
Output Capacity | 20 | -45 | |
| Overall Result | 3 wins | of 5 | 2 wins |
30
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0
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0
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Mistral AI
Microsoft
Ministral 3 14B 2512 saves you $63.00/month
That's $756.00/year compared to WizardLM-2 8x22B at your current usage level of 100K calls/month.
| Metric | Ministral 3 14B 2512 | WizardLM-2 8x22B | Winner |
|---|---|---|---|
| Overall Score | 70 | 34 | Ministral 3 14B 2512 |
| Rank | #121 | #290 | Ministral 3 14B 2512 |
| Quality Rank | #121 | #290 | Ministral 3 14B 2512 |
| Adoption Rank | #121 | #290 | Ministral 3 14B 2512 |
| Parameters | 14B | 22B | -- |
| Context Window | 262K | 66K | Ministral 3 14B 2512 |
| Pricing | $0.20/$0.20/M | $0.62/$0.62/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 17 | Ministral 3 14B 2512 |
| Pricing | 0 | 1 | WizardLM-2 8x22B |
| Context window size | 86 | 76 | Ministral 3 14B 2512 |
| Recency | 100 | 6 | Ministral 3 14B 2512 |
| Output Capacity | 20 | 65 | WizardLM-2 8x22B |
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 34/100 (rank #290), placing it in the top 0% of all 290 models tracked.
Ministral 3 14B 2512 has a 37-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Ministral 3 14B 2512 offers 68% better value per quality point. At 1M tokens/day, you'd spend $6.00/month with Ministral 3 14B 2512 vs $18.60/month with WizardLM-2 8x22B — a $12.60 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. 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 clearly outperforms WizardLM-2 8x22B with a significant 36.5-point lead. For most general use cases, Ministral 3 14B 2512 is the stronger choice. However, WizardLM-2 8x22B may still excel in niche scenarios.
Best for Quality
Ministral 3 14B 2512
Marginally better benchmark scores; both are excellent
Best for Cost
Ministral 3 14B 2512
68% 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 | WizardLM-2 8x22B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Mistral AI
Microsoft
Ministral 3 14B 2512 saves you $1.26/month
That's 68% cheaper than WizardLM-2 8x22B 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 | WizardLM-2 8x22B |
|---|---|---|
| Context Window | 262K | 66K |
| Max Output Tokens | -- | 8,000 |
| Open Source | Yes | Yes |
| Created | Dec 2, 2025 | Apr 16, 2024 |
Ministral 3 14B 2512 scores 70/100 (rank #121) compared to WizardLM-2 8x22B's 34/100 (rank #290), giving it a 37-point advantage. Ministral 3 14B 2512 is the stronger overall choice, though WizardLM-2 8x22B may excel in specific areas like certain benchmarks.
Ministral 3 14B 2512 is ranked #121 and WizardLM-2 8x22B is ranked #290 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 WizardLM-2 8x22B's $0.62/M output tokens — 3.1x more expensive. Input token pricing: Ministral 3 14B 2512 at $0.20/M vs WizardLM-2 8x22B at $0.62/M.
Ministral 3 14B 2512 has a larger context window of 262,144 tokens compared to WizardLM-2 8x22B's 65,535 tokens. A larger context window means the model can process longer documents and conversations.