Claude 3 Haiku vs Phi-4-multimodal-instruct
Claude 3 Haiku and Phi-4-multimodal-instruct are closely matched at -0.8 and 3.4 on the LLM Stats Score. Phi-4-multimodal-instruct is 8.0x cheaper per token.
Anthropic · Microsoft · Updated for 2026
Which is better?
Claude 3 Haiku and Phi-4-multimodal-instruct are closely matched on the overall LLM Stats Score at -0.8 and 3.4.
On price, Phi-4-multimodal-instruct is roughly 8.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Claude 3 Haiku also accepts a larger context window (200,000 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 Claude 3 Haiku
- you process long inputs — it offers a 200,000 token context window
Choose Phi-4-multimodal-instruct
- cost matters — it's about 8.0x cheaper per token
- you want the most recent training data — it shipped Feb 2025
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
10 reported for Claude 3 Haiku · 15 for Phi-4-multimodal-instruct
Claude 3 Haiku and Phi-4-multimodal-instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Claude 3 Haiku ($0.25/1M tokens) is 5.0x more expensive than Phi-4-multimodal-instruct ($0.05/1M tokens).
For output processing, Claude 3 Haiku ($1.25/1M tokens) is 12.5x more expensive than Phi-4-multimodal-instruct ($0.10/1M tokens).
In conclusion, Claude 3 Haiku is more expensive than Phi-4-multimodal-instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Claude 3 Haiku accepts 200,000 input tokens compared to Phi-4-multimodal-instruct's 128,000 tokens. Claude 3 Haiku can generate longer responses up to 200,000 tokens, while Phi-4-multimodal-instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both Claude 3 Haiku and Phi-4-multimodal-instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Claude 3 Haiku
Phi-4-multimodal-instruct
License
Usage and distribution terms
Claude 3 Haiku is licensed under a proprietary license, while Phi-4-multimodal-instruct uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
Claude 3 Haiku was released on 2024-03-13, while Phi-4-multimodal-instruct was released on 2025-02-01.
Phi-4-multimodal-instruct is 11 months newer than Claude 3 Haiku.
Mar 13, 2024
2.5 years ago
Feb 1, 2025
1.6 years ago
10mo newerKnowledge Cutoff
When training data ends
Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while Claude 3 Haiku'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 Claude 3 Haiku's cutoff date.
—
Jun 2024
Provider Availability
Claude 3 Haiku is available from Anthropic, Bedrock, Google. Phi-4-multimodal-instruct is available from DeepInfra.
Claude 3 Haiku
Phi-4-multimodal-instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Claude 3 Haiku and Phi-4-multimodal-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Claude 3 Haiku vs Phi-4-multimodal-instruct.