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DeepSeek-V4.1-Flash-1017 vs Step-3.5-Flash

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 37.0. Step-3.5-Flash is 3.0x cheaper per token.

DeepSeek · StepFun · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 37.0, ranking #15 overall.

On price, Step-3.5-Flash 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 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
  • 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 Step-3.5-Flash

  • cost matters — it's about 3.0x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Step-3.5-Flash
StepFun
Core performance indexes
LLM Stats Score
51.0
#15
37.0
#86
Reasoning
48.6
#18
37.0
#86
Coding
39.1
#15
20.5
#113
Agents
38.6
#9
15.4
#106
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
$0.10 / M
Output price
$1.20 / M
$0.40 / M
Context window
1,048,576
65,536

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4.1-Flash-1017
Step-3.5-Flash
Math
31.8#67
33.9#53
Tool use
30.9#7
13.3#115
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 7 for Step-3.5-Flash

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and Step-3.5-Flashdon'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

Step-3.5-Flash costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 3.0x more expensive than Step-3.5-Flash ($0.10/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 3.0x more expensive than Step-3.5-Flash ($0.40/1M tokens).

In conclusion, DeepSeek-V4.1-Flash-1017 is more expensive than Step-3.5-Flash.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Mon Oct 19 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
StepFun
Step-3.5-Flash
Input tokens$0.10
Output tokens$0.40
Best providerStepFun
Notice missing or incorrect data?

Model Size

Parameter count comparison

567.2B diff

DeepSeek-V4.1-Flash-1017 has 567.2B more parameters than Step-3.5-Flash, making it 289.4% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
StepFun
Step-3.5-Flash
196.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
196.0B
Step-3.5-Flash

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to Step-3.5-Flash's 65,536 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Step-3.5-Flash is limited to 8,192 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
StepFun
Step-3.5-Flash
Input65,536 tokens
Output8,192 tokens
Mon Oct 19 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas Step-3.5-Flash 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

Text
Images
Audio
Video

Step-3.5-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while Step-3.5-Flash uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V4.1-Flash-1017

MIT

Open weights

Step-3.5-Flash

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Step-3.5-Flash was released on 2026-02-02.

DeepSeek-V4.1-Flash-1017 is 9 months newer than Step-3.5-Flash.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

8mo newer
Step-3.5-Flash

Feb 2, 2026

8 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-V4.1-Flash-1017 is available from DeepSeek. Step-3.5-Flash is available from StepFun.

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Step-3.5-Flash

stepfun logo
StepFun
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and Step-3.5-Flash side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Step-3.5-Flash
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Step-3.5-Flash.

Which is better, DeepSeek-V4.1-Flash-1017 or Step-3.5-Flash?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 37.0. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and Step-3.5-Flash is made by StepFun. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4.1-Flash-1017 compare to Step-3.5-Flash in benchmarks?

DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%. Step-3.5-Flash scores AIME 2025: 97.3%, Tau-bench: 88.2%, LiveCodeBench v6: 86.4%, IMO-AnswerBench: 85.4%, SWE-Bench Verified: 74.4%.

Is DeepSeek-V4.1-Flash-1017 cheaper than Step-3.5-Flash?

Step-3.5-Flash is 3.0x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. Step-3.5-Flash costs $0.10/M input and $0.40/M output via stepfun.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and Step-3.5-Flash?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and Step-3.5-Flash supports 66K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4.1-Flash-1017 and Step-3.5-Flash?

Key differences include LLM Stats Score (51.0 vs 37.0), context window (1.0M vs 66K), input pricing ($0.30 vs $0.10/M), multimodal support (yes vs no), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and Step-3.5-Flash?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Step-3.5-Flash is developed by StepFun.

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