| Signal | Phi 4 | Delta | Qwen3.5-122B-A10B |
|---|---|---|---|
Capabilities | 33 | -50 | |
Benchmarks | 73 | +4 | |
Pricing | 100 | +2 | |
Context window size | 67 | -19 | |
Recency | 51 | -49 | |
Output Capacity | 70 | -10 | |
| Overall Result | 2 wins | of 6 | 4 wins |
Score History
70.5
current score
Phi 4
right now
70.4
current score
Microsoft
Alibaba
Phi 4 saves you $116.50/month
That's $1398.00/year compared to Qwen3.5-122B-A10B at your current usage level of 100K calls/month.
| Metric | Phi 4 | Qwen3.5-122B-A10B | Winner |
|---|---|---|---|
| Overall Score | 71 | 70 | Phi 4 |
| Rank | #56 | #57 | Phi 4 |
| Quality Rank | #56 | #57 | Phi 4 |
| Adoption Rank | #56 | #57 | Phi 4 |
| Parameters | -- | 122B | -- |
| Context Window | 16K | 262K | Qwen3.5-122B-A10B |
| Pricing | $0.07/$0.14/M | $0.26/$2.08/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 83 | Qwen3.5-122B-A10B |
| Benchmarks | 73 | 69 | Phi 4 |
| Pricing | 100 | 98 | Phi 4 |
| Context window size | 67 | 86 | Qwen3.5-122B-A10B |
| Recency | 51 | 100 | Qwen3.5-122B-A10B |
| Output Capacity | 70 | 80 | Qwen3.5-122B-A10B |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Here's what the scores mean for these two models:
Scores 71/100 (rank #56), placing it in the top 81% of all 290 models tracked.
Scores 70/100 (rank #57), placing it in the top 81% 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.
Phi 4 offers 91% better value per quality point. At 1M tokens/day, you'd spend $3.08/month with Phi 4 vs $35.10/month with Qwen3.5-122B-A10B - a $32.02 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 (262K 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 (71/100) 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
Phi 4 and Qwen3.5-122B-A10B are extremely close in overall performance (only 0.09999999999999432 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Phi 4
Marginally better benchmark scores; both are excellent
Best for Cost
Phi 4
91% lower pricing; better value at scale
Best for Reliability
Phi 4
Higher uptime and faster response speeds
Best for Prototyping
Phi 4
Stronger community support and better developer experience
Best for Production
Phi 4
Wider enterprise adoption and proven at scale
by Microsoft
| Capability | Phi 4 | Qwen3.5-122B-A10B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Microsoft
Alibaba
Phi 4 saves you $2.68/month
That's 90% cheaper than Qwen3.5-122B-A10B 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 | Phi 4 | Qwen3.5-122B-A10B |
|---|---|---|
| Context Window | 16K | 262K |
| Max Output Tokens | 16,384 | 65,536 |
| Open Source | Yes | Yes |
| Created | Jan 10, 2025 | Feb 25, 2026 |
Phi 4 scores 71/100 (rank #56) compared to Qwen3.5-122B-A10B's 70/100 (rank #57), giving it a 0-point advantage. Phi 4 is the stronger overall choice, though Qwen3.5-122B-A10B may excel in specific areas like certain benchmarks.
Phi 4 is ranked #56 and Qwen3.5-122B-A10B is ranked #57 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Phi 4 is cheaper at $0.14/M output tokens vs Qwen3.5-122B-A10B's $2.08/M output tokens - 14.9x more expensive. Input token pricing: Phi 4 at $0.07/M vs Qwen3.5-122B-A10B at $0.26/M.
Qwen3.5-122B-A10B has a larger context window of 262,144 tokens compared to Phi 4's 16,384 tokens. A larger context window means the model can process longer documents and conversations.