Model Comparison
DeepSeek-V4-Flash-0731 vs Llama 3.1 70B InstructWhich is better in 2026?
Comparing DeepSeek-V4-Flash-0731 and Llama 3.1 70B Instruct across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-V4-Flash-0731 vs Llama 3.1 70B Instruct — which is better?
DeepSeek-V4-Flash-0731 (by DeepSeek) and Llama 3.1 70B Instruct (by Meta) 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, DeepSeek-V4-Flash-0731 is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0731 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V4-Flash-0731 if…
- cost matters — it's about 1.8x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
Choose Llama 3.1 70B Instruct if…
- you want predictable pricing at $0.20/M input and $0.20/M output
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0731 and Llama 3.1 70B 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-V4-Flash-0731 ($0.09/1M tokens) is 2.2x cheaper than Llama 3.1 70B Instruct ($0.20/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 1.1x cheaper than Llama 3.1 70B Instruct ($0.20/1M tokens).
In conclusion, Llama 3.1 70B Instruct is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Flash-0731 has 234.0B more parameters than Llama 3.1 70B Instruct, making it 334.3% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to Llama 3.1 70B Instruct's 128,000 tokens. Llama 3.1 70B Instruct can generate longer responses up to 128,000 tokens, while DeepSeek-V4-Flash-0731 is limited to 65,536 tokens.
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 is licensed under MIT, while Llama 3.1 70B Instruct uses Llama 3.1 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Llama 3.1 Community License
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Llama 3.1 70B Instruct was released on 2024-07-23.
DeepSeek-V4-Flash-0731 is 25 months newer than Llama 3.1 70B Instruct.
Jul 31, 2026
3 days ago
2.0yr newerJul 23, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Fireworks, Novita. Llama 3.1 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Cerebras, Together, Fireworks, Bedrock, Sambanova.
DeepSeek-V4-Flash-0731
Llama 3.1 70B 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-V4-Flash-0731 and Llama 3.1 70B Instruct side-by-side, then vote on the output you prefer.
| Feature | | |
|---|
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Llama 3.1 70B Instruct.