Model Comparison
DeepSeek R1 Distill Llama 70B vs Phi-4-multimodal-instructWhich is better in 2026?
Comparing DeepSeek R1 Distill Llama 70B and Phi-4-multimodal-instruct across benchmarks, pricing, and capabilities.
Verdict: DeepSeek R1 Distill Llama 70B vs Phi-4-multimodal-instruct — which is better?
DeepSeek R1 Distill Llama 70B (by DeepSeek) 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.
On price, Phi-4-multimodal-instruct is roughly 2.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose DeepSeek R1 Distill Llama 70B if…
- you want predictable pricing at $0.10/M input and $0.40/M output
Choose Phi-4-multimodal-instruct if…
- cost matters — it's about 2.8x cheaper per token
- you want the most recent training data — it shipped Feb 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Llama 70B and Phi-4-multimodal-instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek R1 Distill Llama 70B ($0.10/1M tokens) is 2.0x more expensive than Phi-4-multimodal-instruct ($0.05/1M tokens).
For output processing, DeepSeek R1 Distill Llama 70B ($0.40/1M tokens) is 4.0x more expensive than Phi-4-multimodal-instruct ($0.10/1M tokens).
In conclusion, DeepSeek R1 Distill Llama 70B is more expensive than Phi-4-multimodal-instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek R1 Distill Llama 70B has 65.0B more parameters than Phi-4-multimodal-instruct, making it 1160.7% larger.
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.
Input Capabilities
Supported data types and modalities
Phi-4-multimodal-instruct supports multimodal inputs, whereas DeepSeek R1 Distill Llama 70B does not.
Phi-4-multimodal-instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Llama 70B
Phi-4-multimodal-instruct
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Llama 70B was released on 2025-01-20, while Phi-4-multimodal-instruct was released on 2025-02-01.
Phi-4-multimodal-instruct is 0 month newer than DeepSeek R1 Distill Llama 70B.
Jan 20, 2025
1.4 years ago
Feb 1, 2025
1.4 years ago
1w newerKnowledge Cutoff
When training data ends
Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while DeepSeek R1 Distill Llama 70B'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 DeepSeek R1 Distill Llama 70B's cutoff date.
—
Jun 2024
Provider Availability
DeepSeek R1 Distill Llama 70B is available from DeepInfra. Phi-4-multimodal-instruct is available from DeepInfra.
DeepSeek R1 Distill Llama 70B
Phi-4-multimodal-instruct
Outputs Comparison
Key Takeaways
No standout differentiators in the data we have for this pair.
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Llama 70B and Phi-4-multimodal-instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek R1 Distill Llama 70B vs Phi-4-multimodal-instruct.