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Phi-3.5-mini-instruct vs Qwen3 VL 8B Instruct

Qwen3 VL 8B Instruct leads the LLM Stats Score 13.9 to -3.8. Phi-3.5-mini-instruct is 1.8x cheaper per token.

Microsoft · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3 VL 8B Instruct leads the overall LLM Stats Score 13.9 to -3.8, ranking #239 overall.

In the 2 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-3.5-mini-instruct is roughly 1.8x 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-3.5-mini-instruct

  • cost matters — it's about 1.8x cheaper per token

Choose Qwen3 VL 8B Instruct

  • overall performance matters — it scores 13.9 and ranks #239 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 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.

Phi-3.5-mini-instruct
Microsoft
Qwen3 VL 8B Instruct
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
-3.8
#345
13.9
#239
Reasoning
-4.7
#341
11.2
#256
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
$0.10 / M
$0.08 / M
Output price
$0.10 / M
$0.50 / M
Context window
128,000
131,072

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Phi-3.5-mini-instruct
Qwen3 VL 8B Instruct
Math
-1.5#304
11.9#235
Finance
0.6#195
15.0#124
Legal
0.6#181
14.5#110
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

31 reported for Phi-3.5-mini-instruct · 46 for Qwen3 VL 8B Instruct

2 shared

Phi-3.5-mini-instruct outperforms in 0 benchmarks, while Qwen3 VL 8B Instruct is better at 2 benchmarks (MMLU, MMLU-Pro).

Qwen3 VL 8B Instruct significantly outperforms across most benchmarks.

Sun Sep 13 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Phi-3.5-mini-instruct costs less

For input processing, Phi-3.5-mini-instruct ($0.10/1M tokens) is 1.3x more expensive than Qwen3 VL 8B Instruct ($0.08/1M tokens).

For output processing, Phi-3.5-mini-instruct ($0.10/1M tokens) is 5.0x cheaper than Qwen3 VL 8B Instruct ($0.50/1M tokens).

In conclusion, Qwen3 VL 8B Instruct is more expensive than Phi-3.5-mini-instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sun Sep 13 2026 • llm-stats.com
Microsoft
Phi-3.5-mini-instruct
Input tokens$0.10
Output tokens$0.10
Best providerAzure
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Instruct
Input tokens$0.08
Output tokens$0.50
Best providerNovita
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

5.2B diff

Qwen3 VL 8B Instruct has 5.2B more parameters than Phi-3.5-mini-instruct, making it 136.8% larger.

Microsoft
Phi-3.5-mini-instruct
3.8Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Instruct
9.0Bparameters
3.8B
Phi-3.5-mini-instruct
9.0B
Qwen3 VL 8B Instruct

Context Window

Maximum input and output token capacity

Qwen3 VL 8B Instruct accepts 131,072 input tokens compared to Phi-3.5-mini-instruct's 128,000 tokens. Phi-3.5-mini-instruct can generate longer responses up to 128,000 tokens, while Qwen3 VL 8B Instruct is limited to 32,768 tokens.

Microsoft
Phi-3.5-mini-instruct
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Instruct
Input131,072 tokens
Output32,768 tokens
Sun Sep 13 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3 VL 8B Instruct supports multimodal inputs, whereas Phi-3.5-mini-instruct does not.

Qwen3 VL 8B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Phi-3.5-mini-instruct

Text
Images
Audio
Video

Qwen3 VL 8B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Phi-3.5-mini-instruct 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.

Phi-3.5-mini-instruct

MIT

Open weights

Qwen3 VL 8B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Phi-3.5-mini-instruct was released on 2024-08-23, while Qwen3 VL 8B Instruct was released on 2025-09-22.

Qwen3 VL 8B Instruct is 13 months newer than Phi-3.5-mini-instruct.

Phi-3.5-mini-instruct

Aug 23, 2024

2.1 years ago

Qwen3 VL 8B Instruct

Sep 22, 2025

11 months ago

1.1yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Phi-3.5-mini-instruct is available from Azure. Qwen3 VL 8B Instruct is available from Novita, DeepInfra.

Phi-3.5-mini-instruct

azure logo
Azure
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M

Qwen3 VL 8B Instruct

novita logo
Novita
Input Price:Input: $0.08/1MOutput Price:Output: $0.50/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $0.69/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Phi-3.5-mini-instruct and Qwen3 VL 8B Instruct side-by-side, then vote on the output you prefer.

Phi-3.5-mini-instruct
✓ Preferred
Qwen3 VL 8B Instruct
Open in Playground

FAQ

Common questions about Phi-3.5-mini-instruct vs Qwen3 VL 8B Instruct.

Which is better, Phi-3.5-mini-instruct or Qwen3 VL 8B Instruct?

Qwen3 VL 8B Instruct leads the LLM Stats Score 13.9 to -3.8. Phi-3.5-mini-instruct is made by Microsoft and Qwen3 VL 8B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Phi-3.5-mini-instruct compare to Qwen3 VL 8B Instruct in benchmarks?

Phi-3.5-mini-instruct scores GSM8k: 86.2%, ARC-C: 84.6%, RULER: 84.1%, PIQA: 81.0%, OpenBookQA: 79.2%. Qwen3 VL 8B Instruct scores DocVQAtest: 96.1%, ScreenSpot: 94.4%, OCRBench: 89.6%, AI2D: 85.7%, MMBench-V1.1: 85.0%.

Is Phi-3.5-mini-instruct cheaper than Qwen3 VL 8B Instruct?

Qwen3 VL 8B Instruct is 1.3x cheaper for input tokens. Phi-3.5-mini-instruct costs $0.10/M input and $0.10/M output via azure. Qwen3 VL 8B Instruct costs $0.08/M input and $0.50/M output via novita.

What are the context window sizes for Phi-3.5-mini-instruct and Qwen3 VL 8B Instruct?

Phi-3.5-mini-instruct supports 128K tokens and Qwen3 VL 8B Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Phi-3.5-mini-instruct and Qwen3 VL 8B Instruct?

Key differences include LLM Stats Score (-3.8 vs 13.9), context window (128K vs 131K), input pricing ($0.10 vs $0.08/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Phi-3.5-mini-instruct and Qwen3 VL 8B Instruct?

Phi-3.5-mini-instruct is developed by Microsoft and Qwen3 VL 8B Instruct is developed by Alibaba Cloud / Qwen Team.

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