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Model comparison

DeepSeek R1 vs GPT-5.6 Terra

DeepSeek against OpenAI, 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

OpenAI

GPT-5.6 Terra

Balanced

AI model capability comparison
SpecificationDeepSeek R1GPT-5.6 Terra
ProviderDeepSeekOpenAI
TierBalancedBalanced
Context window128KWinner: 1.05M
Max output33KWinner: 128K
Input / 1M tokensWinner: $0.55$2
Output / 1M tokensWinner: $2.19$12
WeightsOpenClosed
Parameters671B total / 37B active (MoE)mid-tier reasoning model
Reasoning levelslow, high, maxnone, low, medium, high, xhigh, max
Modalitiestexttext, image
LicenseMITNot disclosedUnverified
API model iddeepseek-reasonergpt-5.6-terra
ReleasedJanuary 20, 2025July 9, 2026
Artificial Analysis Intelligence Index (2026-08-14)42Not verifiedUnverified
Artificial Analysis Intelligence Index [high] (2026-08-14)Not verifiedUnverified50
SWE-bench Verified (2026-09-01)Not verifiedUnverified95.4
Terminal-Bench 2.1 (2026-07-09)Not verifiedUnverified87.4
LiveBench (2026-09-05)Not verifiedUnverified77.9

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

  • 2026-09-05: LiveBench official leaderboard (benchmark-owned), max effortContamination-resistant general capability across reasoning, coding, math, data analysis, and language, with monthly question refreshes. Comparability: comparable with caveat — Rolling question set: observations months apart measure different question mixes. Record the measurement date and compare within ~1 month windows.
  • 2026-09-01: vals.ai SWE-bench Verified leaderboard (independent, mini-swe-agent bash-only) (independent; official SWE-bench not published)Real GitHub issue resolution: does the model's patch pass the hidden tests. Comparability: comparable with caveat — Post-audit vendor claims and pre-audit scores sit on different task trust levels; scaffolding (agent harness, compute budget) also dominates results. Never aggregate across scaffolds.
  • 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).
  • 2026-07-09: OpenAI GPT-5.6 announcement (vendor; chart transcribed by Vellum)Agentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.

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. · GPT-5.6 Terra: Launch list was $2.50/$15; cut to $2/$12 on 2026-07-30. Cached input $0.20/MTok; batch $1/$6.

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 3, 2026

GPT-5.6 Terra

GPT-5.6 Terra delivers roughly GPT-5.5-class quality at about half the cost, with the full 1.05M-token context.

Best for

  • Cost-sensitive production
  • Mixed reasoning workloads
  • High-volume agents

Watch out

Quality trails Sol on the hardest tasks; route frontier work to Sol when it matters.

When the cheaper one wins

DeepSeek R1 is cheaper on output at $2.19 per million tokens against $12 for GPT-5.6 Terra — about 5.5×. 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.

Run the model picker

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 · GPT-5.6 Terra

Common questions

DeepSeek R1 vs GPT-5.6 Terra

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

Is DeepSeek R1 or GPT-5.6 Terra cheaper for input?

DeepSeek R1 is cheaper at $0.55 per million input tokens, against $2 for GPT-5.6 Terra — roughly 3.6× 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. GPT-5.6 Terra has tiered pricing: Launch list was $2.50/$15; cut to $2/$12 on 2026-07-30. Cached input $0.20/MTok; batch $1/$6.

Is DeepSeek R1 or GPT-5.6 Terra cheaper for output?

DeepSeek R1 is cheaper at $2.19 per million output tokens, against $12 for GPT-5.6 Terra — roughly 5.5× 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. GPT-5.6 Terra has tiered pricing: Launch list was $2.50/$15; cut to $2/$12 on 2026-07-30. Cached input $0.20/MTok; batch $1/$6.

Which has the larger context window, DeepSeek R1 or GPT-5.6 Terra?

GPT-5.6 Terra 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 GPT-5.6 Terra support the same reasoning levels?

DeepSeek R1 exposes low, high, max, while GPT-5.6 Terra exposes none, low, medium, high, xhigh, max.

Should I use DeepSeek R1 or GPT-5.6 Terra?

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; GPT-5.6 Terra suits cost-sensitive production.

Can I self-host DeepSeek R1 or GPT-5.6 Terra?

DeepSeek R1 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. GPT-5.6 Terra 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 $2 for GPT-5.6 Terra — a 3.6x difference at the headline tier.
  • Context: GPT-5.6 Terra takes 1.05M against 128K for DeepSeek R1 — only decisive if your prompts approach the smaller window.
  • Measured capability: GPT-5.6 Terra leads Artificial Analysis Intelligence Index 50 to 42 (measured 2026-08-14).
  • Deployment: DeepSeek R1 publishes weights you can self-host; the other is API-only.
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