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Model comparison

DeepSeek R1 vs DeepSeek V3.1

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

Catalog record checked September 3, 2026Individual provider fields may changeEvidence confidence: High — 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 output33KWinner: 128K
Input / 1M tokens$0.55Winner: $0.25
Output / 1M tokens$2.19Winner: $0.95
WeightsOpenOpen
Parameters671B total / 37B active (MoE)671B total / 37B active (MoE)
Reasoning levelslow, high, maxlow, high, max
Modalitiestexttext
LicenseMITMIT
API model iddeepseek-reasonerNot publishedUnverified
ReleasedJanuary 20, 2025August 21, 2025
Artificial Analysis Intelligence Index (2026-08-14)42Winner: 44

Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

  • 2026-08-14: Artificial AnalysisComposite index blending reasoning, knowledge, and coding evals into one 0–100 score. Comparability: directly comparable — AA occasionally rebaselines the index scale between snapshots — a score captured on one date is only comparable to same-snapshot scores (check measuredAt).

Pricing tiers: DeepSeek R1: Launch pricing $0.55/$2.19 per MTok (cache hit $0.14). Third-party hosts list ~$0.70/$2.50. Verify which weights a host serves. · DeepSeek V3.1: Third-party hosted ~$0.25/$0.95 per MTok; first-party peak/off-peak rates vary — verify on api-docs.deepseek.com.

BalancedOpen weightsRecord checked September 3, 2026

DeepSeek R1

DeepSeek R1 is the open-weight (MIT) reasoning model — o1-class quality, 128K context.

Best for

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

Watch out

The deepseek-reasoner alias has been remapped to newer models on first-party API; pin the host/checkpoint you cite.

BudgetOpen weightsRecord checked September 3, 2026

DeepSeek V3.1

DeepSeek V3.1 is the open-weight (MIT) general model — 671B/37B MoE, 128K context, strong reasoning at low cost.

Best for

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

Watch out

Self-hosting needs datacentre VRAM; hosted rates differ by provider.

When the cheaper one wins

DeepSeek V3.1 is cheaper on output at $0.95 per million tokens against $2.19 for DeepSeek R1 — about 2.3×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.

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Evidence confidence: High

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

  • Pricing verified on both sides — Input and output rates are verified for both models.
  • 5/5 core specs verified on both sides — All core specifications verified for both models.
  • 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
  • Verified within the last 90 days — Newest catalog check was 8 days 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.

Is DeepSeek R1 or DeepSeek V3.1 cheaper for input?

DeepSeek V3.1 is cheaper at $0.25 per million input tokens, against $0.55 for DeepSeek R1 — roughly 2.2× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; DeepSeek R1 has tiered pricing: Launch pricing $0.55/$2.19 per MTok (cache hit $0.14). Third-party hosts list ~$0.70/$2.50. Verify which weights a host serves. DeepSeek V3.1 has tiered pricing: Third-party hosted ~$0.25/$0.95 per MTok; first-party peak/off-peak rates vary — verify on api-docs.deepseek.com.

Is DeepSeek R1 or DeepSeek V3.1 cheaper for output?

DeepSeek V3.1 is cheaper at $0.95 per million output tokens, against $2.19 for DeepSeek R1 — roughly 2.3× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; DeepSeek R1 has tiered pricing: Launch pricing $0.55/$2.19 per MTok (cache hit $0.14). Third-party hosts list ~$0.70/$2.50. Verify which weights a host serves. DeepSeek V3.1 has tiered pricing: Third-party hosted ~$0.25/$0.95 per MTok; first-party peak/off-peak rates vary — verify on api-docs.deepseek.com.

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.

Do DeepSeek R1 and DeepSeek V3.1 support the same reasoning levels?

Yes — both accept the same effort settings: "low", "high", "max". Higher effort costs more and takes longer, so start low and raise it only where output quality actually improves.

Should I use DeepSeek R1 or DeepSeek V3.1?

DeepSeek R1 is the balanced tier and DeepSeek V3.1 the budget tier. The useful question is whether your hardest task actually fails on the cheaper one — most production volume such as classification, extraction and summarisation does not.

Next step

Choosing between them

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

  • Input price: DeepSeek V3.1 costs $0.25 per 1M tokens versus $0.55 for DeepSeek R1 — a 2.2x difference at the headline tier.
  • Measured capability: DeepSeek V3.1 leads Artificial Analysis Intelligence Index 44 to 42 (measured 2026-08-14).
  • Positioning: DeepSeek R1 sits in the balanced tier, DeepSeek V3.1 in the budget tier — most production volume (classification, extraction, summarisation) does not need the pricier tier.
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