Claude 3.5 Haiku vs DeepSeek-V4.1-Flash-1017
DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 4.8. DeepSeek-V4.1-Flash-1017 is 3.0x cheaper per token.
Anthropic · DeepSeek · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 4.8, ranking #15 overall.
On price, DeepSeek-V4.1-Flash-1017 is roughly 3.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4.1-Flash-1017 also accepts a larger context window (1,048,576 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 want predictable pricing at $0.80/M input and $4.00/M output
Choose DeepSeek-V4.1-Flash-1017
- overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 3.0x 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 Oct 2026
- 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 · 11 for DeepSeek-V4.1-Flash-1017
Claude 3.5 Haiku and DeepSeek-V4.1-Flash-1017don'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 3.5 Haiku ($0.80/1M tokens) is 2.7x more expensive than DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens).
For output processing, Claude 3.5 Haiku ($4.00/1M tokens) is 3.3x more expensive than DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens).
In conclusion, Claude 3.5 Haiku is more expensive than DeepSeek-V4.1-Flash-1017.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to Claude 3.5 Haiku's 200,000 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Claude 3.5 Haiku is limited to 200,000 tokens.
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas Claude 3.5 Haiku does not.
DeepSeek-V4.1-Flash-1017 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Claude 3.5 Haiku
DeepSeek-V4.1-Flash-1017
License
Usage and distribution terms
Claude 3.5 Haiku is licensed under a proprietary license, while DeepSeek-V4.1-Flash-1017 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 3.5 Haiku was released on 2024-10-22, while DeepSeek-V4.1-Flash-1017 was released on 2026-10-17.
DeepSeek-V4.1-Flash-1017 is 24 months newer than Claude 3.5 Haiku.
Oct 22, 2024
2.0 years ago
Oct 17, 2026
2 days ago
2.0yr 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-V4.1-Flash-1017 is available from DeepSeek.
Claude 3.5 Haiku
DeepSeek-V4.1-Flash-1017
Outputs Comparison
Judge for yourself.
Run your own prompts against Claude 3.5 Haiku and DeepSeek-V4.1-Flash-1017 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Claude 3.5 Haiku vs DeepSeek-V4.1-Flash-1017.
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