Model Comparison

DeepSeek-V3 (Mar 24) vs DeepSeek-V3.1

Compare the listed model data for DeepSeek-V3 (Mar 24) by DeepSeek and DeepSeek-V3.1 by DeepSeek. Benchmark and pricing records are not a controlled test and may change.

Data last updated: 2026-10-16. Verify current model details with each provider.

What the listed data says

DeepSeek-V3 (Mar 24): 128K tokens; DeepSeek-V3.1: 128K tokens. The listed context-window values are equal. DeepSeek-V3 (Mar 24) is listed for coding, agentic workflows, long-context tasks; DeepSeek-V3.1 is listed for no specific capability flags. Shared catalog benchmark entries: MMLU: DeepSeek-V3 (Mar 24) 90.5%; DeepSeek-V3.1 91.7%; HumanEval: DeepSeek-V3 (Mar 24) 91.8%; DeepSeek-V3.1 93.8%; LiveCodeBench: DeepSeek-V3 (Mar 24) 62.8%; DeepSeek-V3.1 68.2%; SWE-bench Verified: DeepSeek-V3 (Mar 24) 46.8%; DeepSeek-V3.1 52.3%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.

Catalog source links

Use these model and provider links to verify current specifications, pricing, and availability.

Computed differences from catalog data

  • The listed context windows are 128K tokens and 128K tokens; the larger is 1× the smaller.
  • On shared numeric benchmark entries, MMLU: DeepSeek-V3 (Mar 24) − DeepSeek-V3.1 = -1.2 percentage points (90.5% vs 91.7%); HumanEval: DeepSeek-V3 (Mar 24) − DeepSeek-V3.1 = -2 percentage points (91.8% vs 93.8%); LiveCodeBench: DeepSeek-V3 (Mar 24) − DeepSeek-V3.1 = -5.4 percentage points (62.8% vs 68.2%); SWE-bench Verified: DeepSeek-V3 (Mar 24) − DeepSeek-V3.1 = -5.5 percentage points (46.8% vs 52.3%).
  • The first listed parameter quantities are 671B total (37B active via MoE) and 671B total (37B active via MoE); the larger quantity is 1× the smaller. Total and active MoE parameters are not directly equivalent.
  • The catalog release dates are March 2025 and June 2025, about 3 months apart at the precision supplied.

Cost example: 1M input and 1M output tokens

A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.

Choose DeepSeek-V3 (Mar 24) if…

Choose DeepSeek-V3 (Mar 24) when your task aligns with catalog-listed uses or strengths such as High-quality coding where reasoning mode is unnecessary, Business intelligence and data analysis, RAG pipelines requiring strong comprehension, 62.8% LiveCodeBench — best open non-reasoning coding score at March 2025 release.

Choose DeepSeek-V3.1 if…

Choose DeepSeek-V3.1 when your task aligns with catalog-listed uses or strengths such as Enterprise software development requiring high quality at low latency, Document intelligence and knowledge base applications, API providers serving general business customers, DeepSeek's most capable non-reasoning model as of June 2025.

DeepSeek-V3 (Mar 24)

Browse DeepSeek models

March 2024 DeepSeek-V3 checkpoint — improved coding and reasoning over the original V3 release.

Parameters: 671B total (37B active via MoE)

Context: 128K tokens

Catalog pricing: MIT open source. DeepSeek API: $0.27/MTok input, $1.10/MTok output

DeepSeek Coding · Agentic · Long Context Open Source

View DeepSeek-V3 (Mar 24) model profile

DeepSeek-V3.1

Browse DeepSeek models

DeepSeek-V3.1 — next iteration with improved instruction following, better coding, and stronger general capabilities.

Parameters: 671B total (37B active via MoE)

Context: 128K tokens

Catalog pricing: MIT open source. DeepSeek API: ~$0.27/MTok input, ~$1.10/MTok output

DeepSeek General Purpose Open Source

View DeepSeek-V3.1 model profile

Feature Comparison — DeepSeek-V3 (Mar 24) vs DeepSeek-V3.1

Catalog specifications for DeepSeek-V3 (Mar 24) and DeepSeek-V3.1
Specification DeepSeek-V3 (Mar 24) DeepSeek-V3.1
Provider DeepSeek DeepSeek
Parameters 671B total (37B active via MoE) 671B total (37B active via MoE)
Context window 128K tokens 128K tokens
Maximum output Not listed Not listed
Catalog pricing MIT open source. DeepSeek API: $0.27/MTok input, $1.10/MTok output MIT open source. DeepSeek API: ~$0.27/MTok input, ~$1.10/MTok output
Listed input/output cost per 1M tokens Separate numeric input/output rates not listed Separate numeric input/output rates not listed
License MIT MIT
Coding support Listed Not listed
Reasoning support Not listed Not listed
Vision input Not listed Not listed
Multimodal Not listed Not listed
Open weights Yes Yes
Benchmark: MMLU 90.5% 91.7%
Benchmark: HumanEval 91.8% 93.8%
Benchmark: LiveCodeBench 62.8% 68.2%
Benchmark: SWE-bench Verified 46.8% 52.3%

Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.

Frequently Asked Questions

What is different between DeepSeek-V3 (Mar 24) and DeepSeek-V3.1?
DeepSeek-V3 (Mar 24): 128K tokens; DeepSeek-V3.1: 128K tokens. The listed context-window values are equal. DeepSeek-V3 (Mar 24) is listed for coding, agentic workflows, long-context tasks; DeepSeek-V3.1 is listed for no specific capability flags. Shared catalog benchmark entries: MMLU: DeepSeek-V3 (Mar 24) 90.5%; DeepSeek-V3.1 91.7%; HumanEval: DeepSeek-V3 (Mar 24) 91.8%; DeepSeek-V3.1 93.8%; LiveCodeBench: DeepSeek-V3 (Mar 24) 62.8%; DeepSeek-V3.1 68.2%; SWE-bench Verified: DeepSeek-V3 (Mar 24) 46.8%; DeepSeek-V3.1 52.3%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
What benchmark values are listed for DeepSeek-V3 (Mar 24) and DeepSeek-V3.1?
MMLU: DeepSeek-V3 (Mar 24) 90.5%; DeepSeek-V3.1 91.7%; HumanEval: DeepSeek-V3 (Mar 24) 91.8%; DeepSeek-V3.1 93.8%; LiveCodeBench: DeepSeek-V3 (Mar 24) 62.8%; DeepSeek-V3.1 68.2%; SWE-bench Verified: DeepSeek-V3 (Mar 24) 46.8%; DeepSeek-V3.1 52.3%. The catalog values may use different versions and evaluation setups, so they are reference points rather than a controlled head-to-head result.
Which model has the larger listed context window?
DeepSeek-V3 (Mar 24): 128K tokens; DeepSeek-V3.1: 128K tokens. The listed context-window values are equal.
What are the listed costs per million tokens for DeepSeek-V3 (Mar 24) and DeepSeek-V3.1?
DeepSeek-V3 (Mar 24): Separate numeric input/output rates not listed (MIT open source. DeepSeek API: $0.27/MTok input, $1.10/MTok output). DeepSeek-V3.1: Separate numeric input/output rates not listed (MIT open source. DeepSeek API: ~$0.27/MTok input, ~$1.10/MTok output). Where separate numeric input and output rates are available, the worked example uses 1M input plus 1M output tokens. Confirm current terms with each provider.
How far apart are the listed release dates for DeepSeek-V3 (Mar 24) and DeepSeek-V3.1?
The catalog lists DeepSeek-V3 (Mar 24) as March 2025 and DeepSeek-V3.1 as June 2025, about 3 months apart at the precision supplied.
When was the comparison data last updated?
The model catalog records 2026-10-16 as its data update date. Provider specifications and prices may have changed since then.
How should I choose between DeepSeek-V3 (Mar 24) and DeepSeek-V3.1?
Compare the listed specifications and capabilities, review the benchmark notes, then test both with the same representative prompt for your task. This page does not claim a universal winner.

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