DeepSeek-V4.1-Flash-1017 vs Hermes 3 70B
DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 3.6. DeepSeek-V4.1-Flash-1017 is 1.3x cheaper per token.
DeepSeek · Nous Research · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.2 to 3.6, ranking #15 overall.
On price, DeepSeek-V4.1-Flash-1017 is roughly 1.3x 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 DeepSeek-V4.1-Flash-1017
- overall performance matters — it scores 51.2 and ranks #15 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 1.3x 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
Choose Hermes 3 70B
- you want predictable pricing at $0.70/M input and $0.70/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
11 reported for DeepSeek-V4.1-Flash-1017 · 17 for Hermes 3 70B
DeepSeek-V4.1-Flash-1017 and Hermes 3 70Bdon'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, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 2.3x cheaper than Hermes 3 70B ($0.70/1M tokens).
For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 1.7x more expensive than Hermes 3 70B ($0.70/1M tokens).
In conclusion, Hermes 3 70B is more expensive than DeepSeek-V4.1-Flash-1017.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4.1-Flash-1017 has 693.2B more parameters than Hermes 3 70B, making it 990.3% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to Hermes 3 70B's 131,072 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Hermes 3 70B is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas Hermes 3 70B does not.
DeepSeek-V4.1-Flash-1017 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4.1-Flash-1017
Hermes 3 70B
License
Usage and distribution terms
DeepSeek-V4.1-Flash-1017 is licensed under MIT, while Hermes 3 70B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Hermes 3 70B was released on 2024-08-15.
DeepSeek-V4.1-Flash-1017 is 26 months newer than Hermes 3 70B.
Oct 17, 2026
2 days ago
2.2yr newerAug 15, 2024
2.2 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-V4.1-Flash-1017 is available from DeepSeek. Hermes 3 70B is available from DeepInfra.
DeepSeek-V4.1-Flash-1017
Hermes 3 70B
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash-1017 and Hermes 3 70B side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash-1017 vs Hermes 3 70B.