DeepSeek-V4.1-Flash vs Step 3.7 Flash
DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 30.2. DeepSeek-V4.1-Flash is 1.3x cheaper per token.
DeepSeek · StepFun · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 30.2, ranking #13 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4.1-Flash 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 also accepts a larger context window (1,040,000 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 DeepSeek-V4.1-Flash
- overall performance matters — it scores 51.8 and ranks #13 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 1.3x cheaper per token
- you process long inputs — it offers a 1,040,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Step 3.7 Flash
- you want predictable pricing at $0.20/M input and $1.15/M output
At a glance
The differences that matter most.
Individual benchmarks
20 reported for DeepSeek-V4.1-Flash · 4 for Step 3.7 Flash
DeepSeek-V4.1-Flash outperforms in 1 benchmarks (Terminal-Bench 2.1), while Step 3.7 Flash is better at 0 benchmarks.
DeepSeek-V4.1-Flash 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-V4.1-Flash ($0.22/1M tokens) is 1.1x more expensive than Step 3.7 Flash ($0.20/1M tokens).
For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 1.7x cheaper than Step 3.7 Flash ($1.15/1M tokens).
In conclusion, Step 3.7 Flash is more expensive than DeepSeek-V4.1-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4.1-Flash has 565.2B more parameters than Step 3.7 Flash, making it 285.5% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to Step 3.7 Flash's 262,144 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while Step 3.7 Flash is limited to 262,144 tokens.
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4.1-Flash and Step 3.7 Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash
Step 3.7 Flash
License
Usage and distribution terms
DeepSeek-V4.1-Flash is licensed under MIT, while Step 3.7 Flash 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 was released on 2026-09-10, while Step 3.7 Flash was released on 2026-06-10.
DeepSeek-V4.1-Flash is 3 months newer than Step 3.7 Flash.
Sep 10, 2026
1 weeks ago
3mo newerJun 10, 2026
3 months 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 is available from Fireworks, DeepInfra, DeepSeek, Novita. Step 3.7 Flash is available from DeepInfra.
DeepSeek-V4.1-Flash
Step 3.7 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and Step 3.7 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs Step 3.7 Flash.