| Signal | Mixtral 8x7B Instruct | Delta | Phi 4 |
|---|---|---|---|
Capabilities | 50 | +17 | |
Pricing | 1 | +0 | |
Context window size | 72 | +5 | |
Recency | 0 | -55 | |
Output Capacity | 70 | -- | |
Benchmarks | 0 | -32 | |
| Overall Result | 3 wins | of 6 | 2 wins |
14
days ranked higher
4
days
12
days ranked higher
Mistral AI
Microsoft
Phi 4 saves you $68.00/month
That's $816.00/year compared to Mixtral 8x7B Instruct at your current usage level of 100K calls/month.
| Metric | Mixtral 8x7B Instruct | Phi 4 | Winner |
|---|---|---|---|
| Overall Score | 47 | 46 | Mixtral 8x7B Instruct |
| Rank | #258 | #261 | Mixtral 8x7B Instruct |
| Quality Rank | #258 | #261 | Mixtral 8x7B Instruct |
| Adoption Rank | #258 | #261 | Mixtral 8x7B Instruct |
| Parameters | 7B | -- | -- |
| Context Window | 33K | 16K | Mixtral 8x7B Instruct |
| Pricing | $0.54/$0.54/M | $0.06/$0.14/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 33 | Mixtral 8x7B Instruct |
| Pricing | 1 | 0 | Mixtral 8x7B Instruct |
| Context window size | 72 | 67 | Mixtral 8x7B Instruct |
| Recency | 0 | 55 | Phi 4 |
| Output Capacity | 70 | 70 | Mixtral 8x7B Instruct |
| Benchmarks | -- | 32 | Phi 4 |
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 47/100 (rank #258), placing it in the top 11% of all 290 models tracked.
Scores 46/100 (rank #261), placing it in the top 10% of all 290 models tracked.
With only a 2-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.
Phi 4 offers 81% better value per quality point. At 1M tokens/day, you'd spend $3.00/month with Phi 4 vs $16.20/month with Mixtral 8x7B Instruct — a $13.20 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. Phi 4 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (33K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.14/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (47/100) correlates with better nuance, coherence, and style in long-form content
Mixtral 8x7B Instruct and Phi 4 are extremely close in overall performance (only 1.5 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Mixtral 8x7B Instruct
Marginally better benchmark scores; both are excellent
Best for Cost
Phi 4
81% lower pricing; better value at scale
Best for Reliability
Mixtral 8x7B Instruct
Higher uptime and faster response speeds
Best for Prototyping
Mixtral 8x7B Instruct
Stronger community support and better developer experience
Best for Production
Mixtral 8x7B Instruct
Wider enterprise adoption and proven at scale
by Mistral AI
| Capability | Mixtral 8x7B Instruct | Phi 4 |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Mistral AI
Microsoft
Phi 4 saves you $1.34/month
That's 83% cheaper than Mixtral 8x7B 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 | Mixtral 8x7B Instruct | Phi 4 |
|---|---|---|
| Context Window | 33K | 16K |
| Max Output Tokens | 16,384 | 16,384 |
| Open Source | Yes | Yes |
| Created | Dec 10, 2023 | Jan 10, 2025 |
Mixtral 8x7B Instruct scores 47/100 (rank #258) compared to Phi 4's 46/100 (rank #261), giving it a 2-point advantage. Mixtral 8x7B Instruct is the stronger overall choice, though Phi 4 may excel in specific areas like cost efficiency.
Mixtral 8x7B Instruct is ranked #258 and Phi 4 is ranked #261 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.
Phi 4 is cheaper at $0.14/M output tokens vs Mixtral 8x7B Instruct's $0.54/M output tokens — 3.9x more expensive. Input token pricing: Mixtral 8x7B Instruct at $0.54/M vs Phi 4 at $0.06/M.
Mixtral 8x7B Instruct has a larger context window of 32,768 tokens compared to Phi 4's 16,384 tokens. A larger context window means the model can process longer documents and conversations.