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DeepSeek-V4.1-Flash-1017 vs Qwen3 VL 235B A22B Instruct

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 24.4. Qwen3 VL 235B A22B Instruct is 1.4x cheaper per token.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 24.4, ranking #15 overall.

On price, Qwen3 VL 235B A22B Instruct is roughly 1.4x 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 agents — 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 Qwen3 VL 235B A22B Instruct

  • cost matters — it's about 1.4x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Qwen3 VL 235B A22B Instruct
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
51.0
#15
24.4
#184
Reasoning
48.6
#18
22.3
#193
Agents
38.6
#9
12.6
#122
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
$0.20 / M
Output price
$1.20 / M
$0.88 / M
Context window
1,048,576
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
DeepSeek-V4.1-Flash-1017
Qwen3 VL 235B A22B Instruct
Math
31.8#67
23.8#133
Vision
32.2#26
17.9#99
Multimodal
35.0#14
20.4#82
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 50 for Qwen3 VL 235B A22B Instruct

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and Qwen3 VL 235B A22B Instructdon'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

Qwen3 VL 235B A22B Instruct costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 1.5x more expensive than Qwen3 VL 235B A22B Instruct ($0.20/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 1.4x more expensive than Qwen3 VL 235B A22B Instruct ($0.88/1M tokens).

In conclusion, DeepSeek-V4.1-Flash-1017 is more expensive than Qwen3 VL 235B A22B Instruct.*

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

Lowest available price from all providers
Wed Oct 21 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Instruct
Input tokens$0.20
Output tokens$0.88
Best providerDeepinfra
Notice missing or incorrect data?

Model Size

Parameter count comparison

527.2B diff

DeepSeek-V4.1-Flash-1017 has 527.2B more parameters than Qwen3 VL 235B A22B Instruct, making it 223.4% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Instruct
236.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
236.0B
Qwen3 VL 235B A22B Instruct

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to Qwen3 VL 235B A22B Instruct's 262,144 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Qwen3 VL 235B A22B Instruct is limited to 262,144 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Instruct
Input262,144 tokens
Output262,144 tokens
Wed Oct 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and Qwen3 VL 235B A22B Instruct support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

Qwen3 VL 235B A22B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while Qwen3 VL 235B A22B Instruct 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

Qwen3 VL 235B A22B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Qwen3 VL 235B A22B Instruct was released on 2025-09-22.

DeepSeek-V4.1-Flash-1017 is 13 months newer than Qwen3 VL 235B A22B Instruct.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

1.1yr newer
Qwen3 VL 235B A22B Instruct

Sep 22, 2025

1.1 years 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. Qwen3 VL 235B A22B Instruct is available from DeepInfra, Novita.

DeepSeek-V4.1-Flash-1017

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

Qwen3 VL 235B A22B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.20/1MOutput Price:Output: $0.88/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.50/1M
* 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 Qwen3 VL 235B A22B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Qwen3 VL 235B A22B Instruct
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Qwen3 VL 235B A22B Instruct.

Which is better, DeepSeek-V4.1-Flash-1017 or Qwen3 VL 235B A22B Instruct?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 24.4. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and Qwen3 VL 235B A22B Instruct is made by Alibaba Cloud / Qwen Team. 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 Qwen3 VL 235B A22B Instruct 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%. Qwen3 VL 235B A22B Instruct scores DocVQAtest: 97.1%, ScreenSpot: 95.4%, MMLU-Redux: 92.2%, OCRBench: 92.0%, MMBench-V1.1: 89.9%.

Is DeepSeek-V4.1-Flash-1017 cheaper than Qwen3 VL 235B A22B Instruct?

Qwen3 VL 235B A22B Instruct is 1.5x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. Qwen3 VL 235B A22B Instruct costs $0.20/M input and $0.88/M output via deepinfra.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and Qwen3 VL 235B A22B Instruct?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and Qwen3 VL 235B A22B Instruct supports 262K 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 Qwen3 VL 235B A22B Instruct?

Key differences include LLM Stats Score (51.0 vs 24.4), context window (1.0M vs 262K), input pricing ($0.30 vs $0.20/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and Qwen3 VL 235B A22B Instruct?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Qwen3 VL 235B A22B Instruct is developed by Alibaba Cloud / Qwen Team.

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