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DeepSeek-V4-Flash-Max vs Qwen3.6-27B

DeepSeek-V4-Flash-Max leads the LLM Stats Score 39.1 to 35.5. DeepSeek-V4-Flash-Max is 9.2x cheaper per token.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V4-Flash-Max leads the overall LLM Stats Score 39.1 to 35.5, ranking #61 overall.

In the 9 individual benchmarks reported for both models, DeepSeek-V4-Flash-Max wins 6; this is a narrower head-to-head signal than the composite indexes.

On price, DeepSeek-V4-Flash-Max is roughly 9.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4-Flash-Max 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-Flash-Max

  • overall performance matters — it scores 39.1 and ranks #61 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 6 of 9 exact shared results
  • cost matters — it's about 9.2x 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 Apr 2026

Choose Qwen3.6-27B

  • you want predictable pricing at $0.32/M input and $3.20/M output

At a glance

The differences that matter most.

Core performance indexes
39.1
#61
35.5
#83
39.8
#56
36.2
#75
28.8
#56
25.9
#67
18.3
#68
16.1
#79
Cost, coverage & limits
Benchmark wins
6 of 9
3 of 9
Input price
$0.09 / M
$0.32 / M
Output price
$0.18 / M
$3.20 / M
Context window
1,048,576
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4-Flash-Max
Qwen3.6-27B
39.2#21
34.2#48
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

19 reported for DeepSeek-V4-Flash-Max · 44 for Qwen3.6-27B

9 shared

DeepSeek-V4-Flash-Max outperforms in 6 benchmarks (GPQA, HMMT Feb 26, Humanity's Last Exam, IMO-AnswerBench, SWE-bench Multilingual, SWE-Bench Verified), while Qwen3.6-27B is better at 2 benchmarks (SWE-Bench Pro, Terminal-Bench 2.0).

DeepSeek-V4-Flash-Max shows notably better performance in the majority of benchmarks.

Mon Sep 21 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

DeepSeek-V4-Flash-Max costs less

For input processing, DeepSeek-V4-Flash-Max ($0.09/1M tokens) is 3.6x cheaper than Qwen3.6-27B ($0.32/1M tokens).

For output processing, DeepSeek-V4-Flash-Max ($0.18/1M tokens) is 17.8x cheaper than Qwen3.6-27B ($3.20/1M tokens).

In conclusion, Qwen3.6-27B is more expensive than DeepSeek-V4-Flash-Max.*

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

Lowest available price from all providers
Mon Sep 21 2026 • llm-stats.com
DeepSeek
DeepSeek-V4-Flash-Max
Input tokens$0.09
Output tokens$0.18
Best providerDeepinfra
Alibaba Cloud / Qwen Team
Qwen3.6-27B
Input tokens$0.32
Output tokens$3.20
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

256.2B diff

DeepSeek-V4-Flash-Max has 256.2B more parameters than Qwen3.6-27B, making it 922.3% larger.

DeepSeek
DeepSeek-V4-Flash-Max
284.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.6-27B
27.8Bparameters
284.0B
DeepSeek-V4-Flash-Max
27.8B
Qwen3.6-27B

Context Window

Maximum input and output token capacity

DeepSeek-V4-Flash-Max accepts 1,048,576 input tokens compared to Qwen3.6-27B's 262,144 tokens. DeepSeek-V4-Flash-Max can generate longer responses up to 1,048,576 tokens, while Qwen3.6-27B is limited to 262,144 tokens.

DeepSeek
DeepSeek-V4-Flash-Max
Input1,048,576 tokens
Output1,048,576 tokens
Alibaba Cloud / Qwen Team
Qwen3.6-27B
Input262,144 tokens
Output262,144 tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.6-27B supports multimodal inputs, whereas DeepSeek-V4-Flash-Max does not.

Qwen3.6-27B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4-Flash-Max

Text
Images
Audio
Video

Qwen3.6-27B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4-Flash-Max is licensed under MIT, while Qwen3.6-27B uses Apache 2.0.

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

DeepSeek-V4-Flash-Max

MIT

Open weights

Qwen3.6-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-Max was released on 2026-04-23, while Qwen3.6-27B was released on 2026-04-21.

DeepSeek-V4-Flash-Max is 0 month newer than Qwen3.6-27B.

DeepSeek-V4-Flash-Max

Apr 23, 2026

5 months ago

2d newer
Qwen3.6-27B

Apr 21, 2026

5 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-Flash-Max is available from DeepInfra, DeepSeek. Qwen3.6-27B is available from DeepInfra, Novita.

DeepSeek-V4-Flash-Max

deepinfra logo
Deepinfra
Input Price:Input: $0.09/1MOutput Price:Output: $0.18/1M
deepseek logo
DeepSeek
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M

Qwen3.6-27B

deepinfra logo
Deepinfra
Input Price:Input: $0.32/1MOutput Price:Output: $3.20/1M
novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $3.60/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-V4-Flash-Max and Qwen3.6-27B side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-Max
✓ Preferred
Qwen3.6-27B
Open in Playground

FAQ

Common questions about DeepSeek-V4-Flash-Max vs Qwen3.6-27B.

Which is better, DeepSeek-V4-Flash-Max or Qwen3.6-27B?

DeepSeek-V4-Flash-Max leads the LLM Stats Score 39.1 to 35.5. DeepSeek-V4-Flash-Max is made by DeepSeek and Qwen3.6-27B 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-Flash-Max compare to Qwen3.6-27B in benchmarks?

DeepSeek-V4-Flash-Max scores CodeForces: 100.0%, HMMT Feb 26: 94.8%, LiveCodeBench: 91.6%, IMO-AnswerBench: 88.4%, GPQA: 88.1%. Qwen3.6-27B scores CountBench: 97.8%, VLMsAreBlind: 97.0%, V*: 94.7%, AIME 2026: 94.1%, HMMT 2025: 93.8%.

Is DeepSeek-V4-Flash-Max cheaper than Qwen3.6-27B?

DeepSeek-V4-Flash-Max is 3.6x cheaper for input tokens. DeepSeek-V4-Flash-Max costs $0.09/M input and $0.18/M output via deepinfra. Qwen3.6-27B costs $0.32/M input and $3.20/M output via deepinfra.

What are the context window sizes for DeepSeek-V4-Flash-Max and Qwen3.6-27B?

DeepSeek-V4-Flash-Max supports 1.0M tokens and Qwen3.6-27B 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-Flash-Max and Qwen3.6-27B?

Key differences include LLM Stats Score (39.1 vs 35.5), context window (1.0M vs 262K), input pricing ($0.09 vs $0.32/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-Max and Qwen3.6-27B?

DeepSeek-V4-Flash-Max is developed by DeepSeek and Qwen3.6-27B is developed by Alibaba Cloud / Qwen Team.