Phi 4 vs Qwen3 VL 8B Instruct
Qwen3 VL 8B Instruct leads the LLM Stats Score 13.8 to 5.4. Phi 4 is 2.1x cheaper per token.
Microsoft · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 VL 8B Instruct leads the overall LLM Stats Score 13.8 to 5.4, ranking #256 overall.
In the 3 individual benchmarks reported for both models, Qwen3 VL 8B Instruct wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Phi 4 is roughly 2.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 8B Instruct also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Phi 4
- cost matters — it's about 2.1x cheaper per token
Choose Qwen3 VL 8B Instruct
- overall performance matters — it scores 13.8 and ranks #256 on LLM Stats
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
13 reported for Phi 4 · 46 for Qwen3 VL 8B Instruct
Phi 4 outperforms in 1 benchmarks (MMLU), while Qwen3 VL 8B Instruct is better at 2 benchmarks (IFEval, MMLU-Pro).
Qwen3 VL 8B Instruct shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Phi 4 ($0.07/1M tokens) is 1.1x cheaper than Qwen3 VL 8B Instruct ($0.08/1M tokens).
For output processing, Phi 4 ($0.14/1M tokens) is 3.6x cheaper than Qwen3 VL 8B Instruct ($0.50/1M tokens).
In conclusion, Qwen3 VL 8B Instruct is more expensive than Phi 4.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Phi 4 has 5.7B more parameters than Qwen3 VL 8B Instruct, making it 63.3% larger.
Context Window
Maximum input and output token capacity
Qwen3 VL 8B Instruct accepts 131,072 input tokens compared to Phi 4's 16,384 tokens. Qwen3 VL 8B Instruct can generate longer responses up to 32,768 tokens, while Phi 4 is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3 VL 8B Instruct supports multimodal inputs, whereas Phi 4 does not.
Qwen3 VL 8B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
Phi 4
Qwen3 VL 8B Instruct
License
Usage and distribution terms
Phi 4 is licensed under MIT, while Qwen3 VL 8B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Phi 4 was released on 2024-12-12, while Qwen3 VL 8B Instruct was released on 2025-09-22.
Qwen3 VL 8B Instruct is 9 months newer than Phi 4.
Dec 12, 2024
1.8 years ago
Sep 22, 2025
1.0 years ago
9mo newerKnowledge Cutoff
When training data ends
Phi 4 has a documented knowledge cutoff of 2024-06-01, while Qwen3 VL 8B Instruct's cutoff date is not specified.
We can confirm Phi 4's training data extends to 2024-06-01, but cannot make a direct comparison without Qwen3 VL 8B Instruct's cutoff date.
Jun 2024
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Provider Availability
Phi 4 is available from DeepInfra. Qwen3 VL 8B Instruct is available from Novita, DeepInfra.
Phi 4
Qwen3 VL 8B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Phi 4 and Qwen3 VL 8B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Phi 4 vs Qwen3 VL 8B Instruct.