Claude 3.5 Haiku vs DeepSeek-V3
DeepSeek-V3 leads the LLM Stats Score 16.0 to 5.8. DeepSeek-V3 is 3.4x cheaper per token.
Anthropic · DeepSeek · Updated for 2026
Which is better?
DeepSeek-V3 leads the overall LLM Stats Score 16.0 to 5.8, ranking #208 overall.
In the 4 individual benchmarks reported for both models, DeepSeek-V3 wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3 is roughly 3.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Claude 3.5 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 3.5 Haiku
- you process long inputs — it offers a 200,000 token context window
Choose DeepSeek-V3
- overall performance matters — it scores 16.0 and ranks #208 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- cost matters — it's about 3.4x cheaper per token
- you want the most recent training data — it shipped Dec 2024
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for Claude 3.5 Haiku · 20 for DeepSeek-V3
Claude 3.5 Haiku outperforms in 0 benchmarks, while DeepSeek-V3 is better at 4 benchmarks (DROP, GPQA, MMLU-Pro, SWE-Bench Verified).
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, Claude 3.5 Haiku ($0.80/1M tokens) is 3.0x more expensive than DeepSeek-V3 ($0.27/1M tokens).
For output processing, Claude 3.5 Haiku ($4.00/1M tokens) is 3.6x more expensive than DeepSeek-V3 ($1.10/1M tokens).
In conclusion, Claude 3.5 Haiku is more expensive than DeepSeek-V3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Claude 3.5 Haiku accepts 200,000 input tokens compared to DeepSeek-V3's 131,072 tokens. Claude 3.5 Haiku can generate longer responses up to 200,000 tokens, while DeepSeek-V3 is limited to 131,072 tokens.
License
Usage and distribution terms
Claude 3.5 Haiku is licensed under a proprietary license, while DeepSeek-V3 uses MIT + Model License (Commercial use allowed).
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT + Model License (Commercial use allowed)
Open weights
Release Timeline
When each model was launched
Claude 3.5 Haiku was released on 2024-10-22, while DeepSeek-V3 was released on 2024-12-25.
DeepSeek-V3 is 2 months newer than Claude 3.5 Haiku.
Oct 22, 2024
1.9 years ago
Dec 25, 2024
1.7 years ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Claude 3.5 Haiku is available from Bedrock, Google, Anthropic. DeepSeek-V3 is available from DeepSeek.
Claude 3.5 Haiku
DeepSeek-V3
Outputs Comparison
Judge for yourself.
Run your own prompts against Claude 3.5 Haiku and DeepSeek-V3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Claude 3.5 Haiku vs DeepSeek-V3.