Model Comparison

Llama 3.2 90B Instruct vs Phi-4-multimodal-instructWhich is better in 2026?

Llama 3.2 90B Instruct has a slight edge in benchmark performance. Phi-4-multimodal-instruct is 5.8x cheaper per token.

Verdict: Llama 3.2 90B Instruct vs Phi-4-multimodal-instruct — which is better?

Llama 3.2 90B Instruct (by Meta) and Phi-4-multimodal-instruct (by Microsoft) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Llama 3.2 90B Instruct outperforms in 4 benchmarks (AI2D, ChartQA, MMMU, MMMU-Pro), while Phi-4-multimodal-instruct is better at 3 benchmarks (DocVQA, MathVista, TextVQA). Llama 3.2 90B Instruct has a slight edge in benchmark performance.

On price, Phi-4-multimodal-instruct is roughly 5.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Choose Llama 3.2 90B Instruct if…

  • you want the strongest raw capability — it leads on 4 of 7 shared benchmarks

Choose Phi-4-multimodal-instruct if…

  • cost matters — it's about 5.8x cheaper per token
  • you want the most recent training data — it shipped Feb 2025

Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

Llama 3.2 90B Instruct outperforms in 4 benchmarks (AI2D, ChartQA, MMMU, MMMU-Pro), while Phi-4-multimodal-instruct is better at 3 benchmarks (DocVQA, MathVista, TextVQA).

Llama 3.2 90B Instruct has a slight edge in benchmark performance.

Tue Jul 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Phi-4-multimodal-instruct costs less

For input processing, Llama 3.2 90B Instruct ($0.35/1M tokens) is 7.0x more expensive than Phi-4-multimodal-instruct ($0.05/1M tokens).

For output processing, Llama 3.2 90B Instruct ($0.40/1M tokens) is 4.0x more expensive than Phi-4-multimodal-instruct ($0.10/1M tokens).

In conclusion, Llama 3.2 90B Instruct is more expensive than Phi-4-multimodal-instruct.*

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

Lowest available price from all providers
Tue Jul 21 2026 • llm-stats.com
Meta
Llama 3.2 90B Instruct
Input tokens$0.35
Output tokens$0.40
Best providerDeepinfra
Microsoft
Phi-4-multimodal-instruct
Input tokens$0.05
Output tokens$0.10
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

84.4B diff

Llama 3.2 90B Instruct has 84.4B more parameters than Phi-4-multimodal-instruct, making it 1507.1% larger.

Meta
Llama 3.2 90B Instruct
90.0Bparameters
Microsoft
Phi-4-multimodal-instruct
5.6Bparameters
90.0B
Llama 3.2 90B Instruct
5.6B
Phi-4-multimodal-instruct

Context Window

Maximum input and output token capacity

Both models have the same input context window of 128,000 tokens. Both models can generate responses up to 128,000 tokens.

Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Microsoft
Phi-4-multimodal-instruct
Input128,000 tokens
Output128,000 tokens
Tue Jul 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Llama 3.2 90B Instruct and Phi-4-multimodal-instruct support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Llama 3.2 90B Instruct

Text
Images
Audio
Video

Phi-4-multimodal-instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Llama 3.2 90B Instruct is licensed under Llama 3.2, while Phi-4-multimodal-instruct uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Llama 3.2 90B Instruct

Llama 3.2

Open weights

Phi-4-multimodal-instruct

MIT

Open weights

Release Timeline

When each model was launched

Llama 3.2 90B Instruct was released on 2024-09-25, while Phi-4-multimodal-instruct was released on 2025-02-01.

Phi-4-multimodal-instruct is 4 months newer than Llama 3.2 90B Instruct.

Llama 3.2 90B Instruct

Sep 25, 2024

1.8 years ago

Phi-4-multimodal-instruct

Feb 1, 2025

1.5 years ago

4mo newer

Knowledge Cutoff

When training data ends

Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while Llama 3.2 90B Instruct's cutoff date is not specified.

We can confirm Phi-4-multimodal-instruct's training data extends to 2024-06-01, but cannot make a direct comparison without Llama 3.2 90B Instruct's cutoff date.

Llama 3.2 90B Instruct

—

Phi-4-multimodal-instruct

Jun 2024

Provider Availability

Llama 3.2 90B Instruct is available from DeepInfra, Bedrock, Fireworks, Together, Hyperbolic. Phi-4-multimodal-instruct is available from DeepInfra.

Llama 3.2 90B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.35/1MOutput Price:Output: $0.40/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.72/1MOutput Price:Output: $0.72/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
together logo
Together
Input Price:Input: $1.20/1MOutput Price:Output: $1.20/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M

Phi-4-multimodal-instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.05/1MOutput Price:Output: $0.10/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Meta
Higher AI2D score (92.3% vs 82.3%)
Higher ChartQA score (85.5% vs 81.4%)
Higher MMMU score (60.3% vs 55.1%)
Higher MMMU-Pro score (45.2% vs 38.5%)
Microsoft
Less expensive input tokens
Less expensive output tokens
Higher DocVQA score (93.2% vs 90.1%)
Higher MathVista score (62.4% vs 57.3%)
Higher TextVQA score (75.6% vs 73.5%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Llama 3.2 90B Instruct and Phi-4-multimodal-instruct side-by-side, then vote on the output you prefer.

Llama 3.2 90B Instruct
✓ Preferred
Phi-4-multimodal-instruct
Open in Playground
AI Model Comparison Table
Feature
Meta
Llama 3.2 90B Instruct
Microsoft
Phi-4-multimodal-instruct

FAQ

Common questions about Llama 3.2 90B Instruct vs Phi-4-multimodal-instruct.

Which is better, Llama 3.2 90B Instruct or Phi-4-multimodal-instruct?

Llama 3.2 90B Instruct has a slight edge in benchmark performance. Llama 3.2 90B Instruct is made by Meta and Phi-4-multimodal-instruct is made by Microsoft. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Llama 3.2 90B Instruct compare to Phi-4-multimodal-instruct in benchmarks?

Llama 3.2 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%. Phi-4-multimodal-instruct scores ScienceQA Visual: 97.5%, DocVQA: 93.2%, MMBench: 86.7%, POPE: 85.6%, OCRBench: 84.4%.

Is Llama 3.2 90B Instruct cheaper than Phi-4-multimodal-instruct?

Phi-4-multimodal-instruct is 7.0x cheaper for input tokens. Llama 3.2 90B Instruct costs $0.35/M input and $0.40/M output via deepinfra. Phi-4-multimodal-instruct costs $0.05/M input and $0.10/M output via deepinfra.

What are the context window sizes for Llama 3.2 90B Instruct and Phi-4-multimodal-instruct?

Llama 3.2 90B Instruct supports 128K tokens and Phi-4-multimodal-instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Llama 3.2 90B Instruct and Phi-4-multimodal-instruct?

Key differences include input pricing ($0.35 vs $0.05/M), licensing (Llama 3.2 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Llama 3.2 90B Instruct and Phi-4-multimodal-instruct?

Llama 3.2 90B Instruct is developed by Meta and Phi-4-multimodal-instruct is developed by Microsoft.

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