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DeepSeek-V3.2 (Thinking) vs DeepSeek-V4.1-Flash

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 32.6. DeepSeek-V3.2 (Thinking) is 1.0x cheaper per token.

DeepSeek · DeepSeek · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 32.6, ranking #12 overall.

In the 3 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 3; this is a narrower head-to-head signal than the composite indexes.

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-V3.2 (Thinking)

  • you want predictable pricing at $0.28/M input and $0.42/M output

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 3 of 3 exact shared results
  • you process long inputs — it offers a 1,040,000 token context window
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek-V3.2 (Thinking)
DeepSeek
DeepSeek-V4.1-Flash
DeepSeek
Core performance indexes
LLM Stats Score
32.6
#103
51.8
#12
Reasoning
32.6
#101
48.9
#17
Coding
22.9
#78
44.4
#5
Agents
11.2
#110
41.3
#4
Cost, coverage & limits
Benchmark wins
0 of 3
3 of 3
Input price
$0.28 / M
$0.22 / M
Output price
$0.42 / M
$0.66 / M
Context window
131,072
1,040,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V3.2 (Thinking)
DeepSeek-V4.1-Flash
Math
30.2#77
35.2#43
Tool use
10.0#129
35.1#2
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for DeepSeek-V3.2 (Thinking) · 20 for DeepSeek-V4.1-Flash

3 shared

DeepSeek-V3.2 (Thinking) outperforms in 0 benchmarks, while DeepSeek-V4.1-Flash is better at 3 benchmarks (CodeForces, GPQA, 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-V3.2 (Thinking) costs less

For input processing, DeepSeek-V3.2 (Thinking) ($0.28/1M tokens) is 1.3x more expensive than DeepSeek-V4.1-Flash ($0.22/1M tokens).

For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 1.6x cheaper than DeepSeek-V4.1-Flash ($0.66/1M tokens).

In conclusion, DeepSeek-V4.1-Flash is more expensive than DeepSeek-V3.2 (Thinking).*

* 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-V3.2 (Thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
DeepSeek
DeepSeek-V4.1-Flash
Input tokens$0.22
Output tokens$0.66
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

78.2B diff

DeepSeek-V4.1-Flash has 78.2B more parameters than DeepSeek-V3.2 (Thinking), making it 11.4% larger.

DeepSeek
DeepSeek-V3.2 (Thinking)
685.0Bparameters
DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
685.0B
DeepSeek-V3.2 (Thinking)
763.2B
DeepSeek-V4.1-Flash

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to DeepSeek-V3.2 (Thinking)'s 131,072 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while DeepSeek-V3.2 (Thinking) is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Fri Sep 11 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash supports multimodal inputs, whereas DeepSeek-V3.2 (Thinking) does not.

DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.2 (Thinking)

Text
Images
Audio
Video

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek-V3.2 (Thinking)

MIT

Open weights

DeepSeek-V4.1-Flash

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while DeepSeek-V4.1-Flash was released on 2026-09-10.

DeepSeek-V4.1-Flash is 9 months newer than DeepSeek-V3.2 (Thinking).

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

9 months ago

DeepSeek-V4.1-Flash

Sep 10, 2026

0 days ago

9mo newer

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-V3.2 (Thinking) is available from DeepSeek. DeepSeek-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita.

DeepSeek-V3.2 (Thinking)

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

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
* 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-V3.2 (Thinking) and DeepSeek-V4.1-Flash side-by-side, then vote on the output you prefer.

DeepSeek-V3.2 (Thinking)
✓ Preferred
DeepSeek-V4.1-Flash
Open in Playground

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs DeepSeek-V4.1-Flash.

Which is better, DeepSeek-V3.2 (Thinking) or DeepSeek-V4.1-Flash?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 32.6. DeepSeek-V3.2 (Thinking) is made by DeepSeek and DeepSeek-V4.1-Flash is made by DeepSeek. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V3.2 (Thinking) compare to DeepSeek-V4.1-Flash in benchmarks?

DeepSeek-V3.2 (Thinking) scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%. DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%.

Is DeepSeek-V3.2 (Thinking) cheaper than DeepSeek-V4.1-Flash?

DeepSeek-V4.1-Flash is 1.3x cheaper for input tokens. DeepSeek-V3.2 (Thinking) costs $0.28/M input and $0.42/M output via deepseek. DeepSeek-V4.1-Flash costs $0.22/M input and $0.66/M output via fireworks.

What are the context window sizes for DeepSeek-V3.2 (Thinking) and DeepSeek-V4.1-Flash?

DeepSeek-V3.2 (Thinking) supports 131K tokens and DeepSeek-V4.1-Flash supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3.2 (Thinking) and DeepSeek-V4.1-Flash?

Key differences include LLM Stats Score (32.6 vs 51.8), context window (131K vs 1.0M), input pricing ($0.28 vs $0.22/M), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

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