DeepSeek-V3 vs Grok-2
DeepSeek-V3 and Grok-2 are closely matched at 15.8 and 11.6 on the LLM Stats Score. DeepSeek-V3 is 8.4x cheaper per token.
DeepSeek · xAI · Updated for 2026
Which is better?
DeepSeek-V3 and Grok-2 are closely matched on the overall LLM Stats Score at 15.8 and 11.6.
In the 3 individual benchmarks reported for both models, DeepSeek-V3 wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3 is roughly 8.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3 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 DeepSeek-V3
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- cost matters — it's about 8.4x cheaper per token
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Dec 2024
- you need open weights you can self-host or fine-tune
Choose Grok-2
- you want predictable pricing at $2.00/M input and $10.00/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for DeepSeek-V3 · 8 for Grok-2
DeepSeek-V3 outperforms in 3 benchmarks (GPQA, MMLU, MMLU-Pro), while Grok-2 is better at 0 benchmarks.
DeepSeek-V3 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3 ($0.27/1M tokens) is 7.4x cheaper than Grok-2 ($2.00/1M tokens).
For output processing, DeepSeek-V3 ($1.10/1M tokens) is 9.1x cheaper than Grok-2 ($10.00/1M tokens).
In conclusion, Grok-2 is more expensive than DeepSeek-V3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V3 accepts 131,072 input tokens compared to Grok-2's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Grok-2 is limited to 8,000 tokens.
Input capabilities
Documented input modalities across available providers
Grok-2 supports multimodal inputs, whereas DeepSeek-V3 does not.
Grok-2 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3
Grok-2
License
Usage and distribution terms
DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Grok-2 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT + Model License (Commercial use allowed)
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3 was released on 2024-12-25, while Grok-2 was released on 2024-08-13.
DeepSeek-V3 is 4 months newer than Grok-2.
Dec 25, 2024
1.7 years ago
4mo newerAug 13, 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-V3 is available from DeepSeek. Grok-2 is available from xAI.
DeepSeek-V3
Grok-2
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 and Grok-2 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 vs Grok-2.