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DeepSeek-V3.1 vs DeepSeek-V3.2-Exp

DeepSeek-V3.2-Exp leads the LLM Stats Score 28.2 to 22.1. DeepSeek-V3.2-Exp is 1.4x cheaper per token.

DeepSeek · DeepSeek · Updated for 2026

Which is better?

DeepSeek-V3.2-Exp leads the overall LLM Stats Score 28.2 to 22.1, ranking #133 overall.

In the 14 individual benchmarks reported for both models, DeepSeek-V3.2-Exp wins 13; this is a narrower head-to-head signal than the composite indexes.

On price, DeepSeek-V3.2-Exp is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V3.1

  • you want predictable pricing at $0.25/M input and $0.95/M output

Choose DeepSeek-V3.2-Exp

  • overall performance matters — it scores 28.2 and ranks #133 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 13 of 14 exact shared results
  • cost matters — it's about 1.4x cheaper per token
  • you want the most recent training data — it shipped Sep 2025

At a glance

The differences that matter most.

DeepSeek-V3.1
DeepSeek
DeepSeek-V3.2-Exp
DeepSeek
Core performance indexes
LLM Stats Score
22.1
#178
28.2
#133
Reasoning
22.3
#170
28.1
#129
Coding
12.5
#143
17.5
#118
Agents
0.4
#171
6.0
#142
Cost, coverage & limits
Benchmark wins
1 of 14
13 of 14
Input price
$0.25 / M
$0.27 / M
Output price
$0.95 / M
$0.41 / M
Context window
163,840
163,840

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V3.1
DeepSeek-V3.2-Exp
Math
18.7#180
26.3#103
Research
0.8#79
-0.3#80
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

16 reported for DeepSeek-V3.1 · 14 for DeepSeek-V3.2-Exp

14 shared

DeepSeek-V3.1 outperforms in 1 benchmarks (BrowseComp-zh), while DeepSeek-V3.2-Exp is better at 13 benchmarks (Aider-Polyglot, AIME 2025, BrowseComp, CodeForces, GPQA, HMMT 2025, Humanity's Last Exam, LiveCodeBench, MMLU-Pro, SimpleQA, SWE-bench Multilingual, SWE-Bench Verified, Terminal-Bench).

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

Mon Sep 14 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-Exp costs less

For input processing, DeepSeek-V3.1 ($0.25/1M tokens) is 1.1x cheaper than DeepSeek-V3.2-Exp ($0.27/1M tokens).

For output processing, DeepSeek-V3.1 ($0.95/1M tokens) is 2.3x more expensive than DeepSeek-V3.2-Exp ($0.41/1M tokens).

In conclusion, DeepSeek-V3.1 is more expensive than DeepSeek-V3.2-Exp.*

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

Lowest available price from all providers
Mon Sep 14 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.1
Input tokens$0.25
Output tokens$0.95
Best providerDeepinfra
DeepSeek
DeepSeek-V3.2-Exp
Input tokens$0.27
Output tokens$0.41
Best providerNovita
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

14.0B diff

DeepSeek-V3.2-Exp has 14.0B more parameters than DeepSeek-V3.1, making it 2.1% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
671.0B
DeepSeek-V3.1
685.0B
DeepSeek-V3.2-Exp

Context Window

Maximum input and output token capacity

Both models have the same input context window of 163,840 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
Mon Sep 14 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

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

DeepSeek-V3.1

MIT

Open weights

DeepSeek-V3.2-Exp

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while DeepSeek-V3.2-Exp was released on 2025-09-29.

DeepSeek-V3.2-Exp is 9 months newer than DeepSeek-V3.1.

DeepSeek-V3.1

Jan 10, 2025

1.7 years ago

DeepSeek-V3.2-Exp

Sep 29, 2025

11 months ago

8mo 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-V3.1 is available from DeepInfra, Novita. DeepSeek-V3.2-Exp is available from Novita.

DeepSeek-V3.1

deepinfra logo
Deepinfra
Input Price:Input: $0.25/1MOutput Price:Output: $0.95/1M
novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M

DeepSeek-V3.2-Exp

novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $0.41/1M
* 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-V3.1 and DeepSeek-V3.2-Exp side-by-side, then vote on the output you prefer.

DeepSeek-V3.1
✓ Preferred
DeepSeek-V3.2-Exp
Open in Playground

FAQ

Common questions about DeepSeek-V3.1 vs DeepSeek-V3.2-Exp.

Which is better, DeepSeek-V3.1 or DeepSeek-V3.2-Exp?

DeepSeek-V3.2-Exp leads the LLM Stats Score 28.2 to 22.1. DeepSeek-V3.1 is made by DeepSeek and DeepSeek-V3.2-Exp 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-V3.1 compare to DeepSeek-V3.2-Exp in benchmarks?

DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%.

Is DeepSeek-V3.1 cheaper than DeepSeek-V3.2-Exp?

DeepSeek-V3.1 is 1.1x cheaper for input tokens. DeepSeek-V3.1 costs $0.25/M input and $0.95/M output via deepinfra. DeepSeek-V3.2-Exp costs $0.27/M input and $0.41/M output via novita.

What are the context window sizes for DeepSeek-V3.1 and DeepSeek-V3.2-Exp?

DeepSeek-V3.1 supports 164K tokens and DeepSeek-V3.2-Exp supports 164K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3.1 and DeepSeek-V3.2-Exp?

Key differences include LLM Stats Score (22.1 vs 28.2), input pricing ($0.25 vs $0.27/M). See the full comparison above for benchmark-by-benchmark results.

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