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DeepSeek-V4.1-Flash vs Qwen3.5-122B-A10B

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 35.0. DeepSeek-V4.1-Flash is 2.5x cheaper per token.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 35.0, ranking #12 overall.

In the 5 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 4; this is a narrower head-to-head signal than the composite indexes.

On price, DeepSeek-V4.1-Flash is roughly 2.5x 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 #12 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 4 of 5 exact shared results
  • cost matters — it's about 2.5x 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 Qwen3.5-122B-A10B

  • you want predictable pricing at $0.29/M input and $2.40/M output

At a glance

The differences that matter most.

Core performance indexes
51.8
#12
35.0
#88
48.9
#17
35.5
#79
44.4
#5
20.3
#97
41.3
#4
15.6
#82
Cost, coverage & limits
Benchmark wins
4 of 5
1 of 5
Input price
$0.22 / M
$0.29 / M
Output price
$0.66 / M
$2.40 / M
Context window
1,040,000
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

4 shared
Index
DeepSeek-V4.1-Flash
Qwen3.5-122B-A10B
35.2#43
36.1#41
29.5#31
25.8#42
35.1#2
12.2#105
34.3#13
29.1#31
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 81 for Qwen3.5-122B-A10B

5 shared

DeepSeek-V4.1-Flash outperforms in 4 benchmarks (BabyVision, CodeForces, GPQA, ZEROBench), while Qwen3.5-122B-A10B is better at 1 benchmark (Humanity's Last Exam).

DeepSeek-V4.1-Flash significantly outperforms across most benchmarks.

Fri Sep 11 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

DeepSeek-V4.1-Flash costs less

For input processing, DeepSeek-V4.1-Flash ($0.22/1M tokens) is 1.3x cheaper than Qwen3.5-122B-A10B ($0.29/1M tokens).

For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 3.6x cheaper than Qwen3.5-122B-A10B ($2.40/1M tokens).

In conclusion, Qwen3.5-122B-A10B is more expensive than DeepSeek-V4.1-Flash.*

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

Lowest available price from all providers
Fri Sep 11 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash
Input tokens$0.22
Output tokens$0.66
Best providerFireworks
Alibaba Cloud / Qwen Team
Qwen3.5-122B-A10B
Input tokens$0.29
Output tokens$2.40
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

641.2B diff

DeepSeek-V4.1-Flash has 641.2B more parameters than Qwen3.5-122B-A10B, making it 525.6% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Alibaba Cloud / Qwen Team
Qwen3.5-122B-A10B
122.0Bparameters
763.2B
DeepSeek-V4.1-Flash
122.0B
Qwen3.5-122B-A10B

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to Qwen3.5-122B-A10B's 262,144 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while Qwen3.5-122B-A10B is limited to 262,144 tokens.

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Alibaba Cloud / Qwen Team
Qwen3.5-122B-A10B
Input262,144 tokens
Output262,144 tokens
Fri Sep 11 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash and Qwen3.5-122B-A10B support multimodal inputs.

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

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

Qwen3.5-122B-A10B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while Qwen3.5-122B-A10B uses Apache 2.0.

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

DeepSeek-V4.1-Flash

MIT

Open weights

Qwen3.5-122B-A10B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Qwen3.5-122B-A10B was released on 2026-02-24.

DeepSeek-V4.1-Flash is 7 months newer than Qwen3.5-122B-A10B.

DeepSeek-V4.1-Flash

Sep 10, 2026

0 days ago

6mo newer
Qwen3.5-122B-A10B

Feb 24, 2026

6 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 is available from Fireworks, DeepInfra, DeepSeek, Novita. Qwen3.5-122B-A10B is available from DeepInfra, Novita.

DeepSeek-V4.1-Flash

fireworks logo
Fireworks
Input Price:Input: $0.22/1MOutput Price:Output: $0.66/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Qwen3.5-122B-A10B

deepinfra logo
Deepinfra
Input Price:Input: $0.29/1MOutput Price:Output: $2.40/1M
novita logo
Novita
Input Price:Input: $0.40/1MOutput Price:Output: $3.20/1M
* 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-V4.1-Flash and Qwen3.5-122B-A10B side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
Qwen3.5-122B-A10B
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs Qwen3.5-122B-A10B.

Which is better, DeepSeek-V4.1-Flash or Qwen3.5-122B-A10B?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 35.0. DeepSeek-V4.1-Flash is made by DeepSeek and Qwen3.5-122B-A10B 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 compare to Qwen3.5-122B-A10B in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. Qwen3.5-122B-A10B scores CountBench: 97.0%, VLMsAreBlind: 96.7%, MMLU-Redux: 94.0%, IFEval: 93.4%, AI2D: 93.3%.

Is DeepSeek-V4.1-Flash cheaper than Qwen3.5-122B-A10B?

DeepSeek-V4.1-Flash is 1.3x cheaper for input tokens. DeepSeek-V4.1-Flash costs $0.22/M input and $0.66/M output via fireworks. Qwen3.5-122B-A10B costs $0.29/M input and $2.40/M output via deepinfra.

What are the context window sizes for DeepSeek-V4.1-Flash and Qwen3.5-122B-A10B?

DeepSeek-V4.1-Flash supports 1.0M tokens and Qwen3.5-122B-A10B 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 and Qwen3.5-122B-A10B?

Key differences include LLM Stats Score (51.8 vs 35.0), context window (1.0M vs 262K), input pricing ($0.22 vs $0.29/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and Qwen3.5-122B-A10B?

DeepSeek-V4.1-Flash is developed by DeepSeek and Qwen3.5-122B-A10B is developed by Alibaba Cloud / Qwen Team.