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Model comparison

DeepSeek R1 vs Gemini 2.5 Pro

DeepSeek against Google, compared on context, price, and verified benchmark results.

Catalog record checked September 3, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

DeepSeek

DeepSeek R1

Balanced · Open weights

vs

Google

Gemini 2.5 Pro

Balanced

AI model capability comparison
SpecificationDeepSeek R1Gemini 2.5 Pro
ProviderDeepSeekGoogle
TierBalancedBalanced
Context window128KWinner: 1.05M
Max output33KWinner: 66K
Input / 1M tokensWinner: $0.55$1.25
Output / 1M tokensWinner: $2.19$10
WeightsOpenClosed
Parameters671B total / 37B active (MoE)Not disclosedUnverified
Reasoning levelslow, high, maxlow, medium, high
Modalitiestexttext, image, video, audio, pdf
LicenseMITNot disclosedUnverified
API model iddeepseek-reasonergemini-2.5-pro
ReleasedJanuary 20, 2025June 17, 2025
Artificial Analysis Intelligence Index (2026-08-14)42Winner: 47

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. · Gemini 2.5 Pro: $1.25/$10 per MTok (≤200K); $2.50/$15 (>200K). Legacy but still widely listed.

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.

BalancedRecord checked September 2, 2026

Gemini 2.5 Pro

Gemini 2.5 Pro is Google's previous-generation Pro with a 1.05M-token context and strong multimodal support.

Best for

  • Long documents
  • Multimodal input
  • Google Workspace integration

Watch out

A generation behind Gemini 3.x; verify on your workload.

When the cheaper one wins

DeepSeek R1 is cheaper on output at $2.19 per million tokens against $10 for Gemini 2.5 Pro — about 4.6×. 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.
  • 4/5 core specs verified on both sides — Not published for at least one side: parameter count.
  • 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 · Gemini 2.5 Pro

Common questions

DeepSeek R1 vs Gemini 2.5 Pro

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

Is DeepSeek R1 or Gemini 2.5 Pro cheaper for input?

DeepSeek R1 is cheaper at $0.55 per million input tokens, against $1.25 for Gemini 2.5 Pro — 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. Gemini 2.5 Pro has tiered pricing: $1.25/$10 per MTok (≤200K); $2.50/$15 (>200K). Legacy but still widely listed.

Is DeepSeek R1 or Gemini 2.5 Pro cheaper for output?

DeepSeek R1 is cheaper at $2.19 per million output tokens, against $10 for Gemini 2.5 Pro — roughly 4.6× 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. Gemini 2.5 Pro has tiered pricing: $1.25/$10 per MTok (≤200K); $2.50/$15 (>200K). Legacy but still widely listed.

Which has the larger context window, DeepSeek R1 or Gemini 2.5 Pro?

Gemini 2.5 Pro accepts 1.05M tokens against 128K for DeepSeek R1. This only matters if you routinely send very long documents or large codebases.

Do DeepSeek R1 and Gemini 2.5 Pro support the same reasoning levels?

DeepSeek R1 exposes low, high, max, while Gemini 2.5 Pro exposes low, medium, high.

Should I use DeepSeek R1 or Gemini 2.5 Pro?

Both sit in the balanced tier, so the choice usually comes down to price and context rather than capability. DeepSeek R1 suits harder reasoning on a budget; Gemini 2.5 Pro suits long documents.

Can I self-host DeepSeek R1 or Gemini 2.5 Pro?

DeepSeek R1 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. Gemini 2.5 Pro is a closed model whose supported access paths are controlled by its provider.

Next step

Choosing between them

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

  • Input price: DeepSeek R1 costs $0.55 per 1M tokens versus $1.25 for Gemini 2.5 Pro — a 2.3x difference at the headline tier.
  • Context: Gemini 2.5 Pro takes 1.05M against 128K for DeepSeek R1 — only decisive if your prompts approach the smaller window.
  • Measured capability: Gemini 2.5 Pro leads Artificial Analysis Intelligence Index 47 to 42 (measured 2026-08-14).
  • Deployment: DeepSeek R1 publishes weights you can self-host; the other is API-only.
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