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AI Choice Engine

Model comparison

DeepSeek R1 vs DeepSeek V3.1

Two DeepSeek tiers compared on the figures that decide which one a workload actually needs.

DeepSeek R1: profile checked October 25, 2026DeepSeek V3.1: profile checked October 25, 2026Individual provider fields may changeEvidence confidence: Insufficient data — see receipts below

DeepSeek

DeepSeek R1

Balanced · Open weights

vs

DeepSeek

DeepSeek V3.1

Budget · Open weights

AI model capability comparison
SpecificationDeepSeek R1DeepSeek V3.1
ProviderDeepSeekDeepSeek
TierBalancedBudget
Context window128K128K
Max outputNot verifiedUnverifiedNot verifiedUnverified
Input / 1M tokensNot verifiedUnverifiedNot verifiedUnverified
Output / 1M tokensNot verifiedUnverifiedNot verifiedUnverified
WeightsOpenOpen
Parameters671B total / 37B active (MoE)671B total / 37B active (MoE)
Reasoning levelsNot verifiedUnverifiedNot verifiedUnverified
Modalitiestexttext
LicenseMITMIT
ReleasedJanuary 20, 2025August 21, 2025

Dates beside benchmark scores refer to the linked source’s publication or capture date unless that source explicitly states when it measured the result. A shared URL alone does not establish comparable runs; unverified setups are marked. Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Pricing tiers

DeepSeek R1: No current first-party API. The original deepseek-reasoner alias moved to R1-0528 on May 28, 2025 and V3.1 on August 21, 2025, before the alias retired July 24, 2026 at 15:59 UTC. Historical launch tariffs are not verified here; hosts charge their own rates for the MIT weights.

DeepSeek V3.1: No current first-party API or verified third-party tariff. deepseek-chat moved to V3.1-Terminus on September 22, 2025; that alias later retired July 24, 2026. MIT weights remain for self-hosting or separately priced hosts. The original checkpoint's hard output cap and selectable hosted effort menu remain unverified. Current Flash/Pro API prices do not price the original V3.1 checkpoint.

BalancedOpen weightsRecord checked October 25, 2026

DeepSeek R1

DeepSeek R1 is the January 2025 open-weight (MIT) reasoning model — now open weights only, with no first-party API.

Best for

  • Harder reasoning on a budget
  • Open-weight deployments
  • Agentic coding

Watch out

Original January R1 MIT weights remain available. The first-party alias moved to R1-0528 on May 28, 2025 and later to other models before its July 24, 2026 retirement. Pin the exact checkpoint; no current first-party tariff, hard native output cap or selectable hosted effort menu is established for this original profile. Distilled Qwen/Llama variants have additional base-model licence terms.

BudgetOpen weightsRecord checked October 25, 2026

DeepSeek V3.1

DeepSeek V3.1 is a legacy open-weight (MIT) 671B/37B MoE with a 128K context — superseded by V3.1-Terminus, V3.2 and then V4.

Best for

  • Cost-sensitive hosted agents
  • High-volume coding assist
  • Open-weight deployments

Watch out

Legacy: DeepSeek's first-party alias moved to V3.1-Terminus on September 22, 2025. Pin the exact V3.1 checkpoint; current hosted rates depend on provider. The original card supports thinking/non-thinking templates, not a verified selectable low/high/max menu. Self-hosting memory depends on quantization, offloading and hardware. The current first-party pricing table lists Flash-1017 and Pro-0813 only; absence of a third-party tariff here means unknown, not free.

When the cheaper one wins

One of these rows is missing a verified output price, so this page will not name a cheaper winner. Run the model picker against the actual job instead of guessing.

Run the model picker

Evidence confidence: Insufficient data

How strong and complete the evidence behind this comparison is — not a prediction of which model is better. Hard limitations apply: missing pricing; evidence too sparse.

  • Pricing incomplete — No verified token pricing for DeepSeek R1 and DeepSeek V3.1.
  • 3/5 core specs verified on both sides — Not published for at least one side: max output, reasoning levels.
  • No directly aligned benchmark setup — No benchmark has matching cited sources, source dates, units, effort and recorded run details on both models.
  • Verified within the last 90 days — Older of the two catalog checks was 1 day ago.
  • Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Related comparisons

Diving deeper on one model? DeepSeek R1 · DeepSeek V3.1

Common questions

DeepSeek R1 vs DeepSeek V3.1

Answered from the verified figures on this page rather than general guidance.

Which has the larger context window, DeepSeek R1 or DeepSeek V3.1?
Both accept about 128K tokens of context, so document length will not decide between them.
Should I use DeepSeek R1 or DeepSeek V3.1?
We classify DeepSeek R1 in the balanced tier and DeepSeek V3.1 in the budget tier. Test whether either meets your accuracy, tool-use and latency requirements before choosing on price.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

  • Positioning: DeepSeek R1 sits in the balanced tier, DeepSeek V3.1 in the budget tier. Compare accuracy, reliability, latency, and cost on representative tasks before choosing.
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