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Model comparison

DeepSeek V3.1 vs GPT-6 Luna

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

Catalog record checked September 26, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

DeepSeek

DeepSeek V3.1

Budget · Open weights

vs

OpenAI

GPT-6 Luna

Budget

AI model capability comparison
SpecificationDeepSeek V3.1GPT-6 Luna
ProviderDeepSeekOpenAI
TierBudgetBudget
Context window128KWinner: 1.05M
Max outputNot verifiedUnverified128K
Input / 1M tokens$0.25Winner: $0.10
Output / 1M tokens$0.95Winner: $0.50
WeightsOpenClosed
Parameters671B total / 37B active (MoE)GPT-6 low-cost tier
Reasoning levelslow, high, maxnone, low, medium, high, xhigh, max
Modalitiestexttext, image
LicenseMITNot disclosedUnverified
API model idNot publishedUnverifiedgpt-6-luna
ReleasedAugust 21, 2025September 22, 2026
Artificial Analysis Intelligence Index (2026-09-26)13.5Not verifiedUnverified
Artificial Analysis Intelligence Index [max] (2026-09-26)Not verifiedUnverified37.3
DeepSWE 1.1 [max] (2026-09-22)Not verifiedUnverified66.6

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

Where each score comes from, and how far it can be compared across models.

  • 2026-09-26
    Artificial Analysis

    Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.

    Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check measuredAt.

  • 2026-09-22
    OpenAI — Introducing GPT-6 Sol and Luna (vendor; not yet on Datacurve's board)

    Agentic software engineering: pass@1 on real repo tasks with reported cost per completed task.

    Directly comparable

Pricing tiers

DeepSeek V3.1: No first-party API: DeepSeek moved the deepseek-chat alias to V3.1-Terminus on 2025-09-22 (the alias itself was retired on 2026-07-24). Third-party hosts listed ~$0.25/$0.95 per MTok (secondary, last checked 2026-08-29) — verify with your host.

GPT-6 Luna: Direct successor to GPT-5.6 Luna at half the price. Cached input $0.01/MTok; cache writes $0.125. Above 272K input the whole request bills $0.20/$0.75 ($0.02 cached). Batch/Flex $0.05/$0.25; Fast mode $0.20/$1.00. Knowledge cutoff May 18 2026.

BudgetOpen weightsRecord checked September 26, 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 own API stopped serving V3.1 when deepseek-chat moved to V3.1-Terminus on 2025-09-22; hosted rates differ by provider and self-hosting needs datacentre VRAM.

BudgetRecord checked September 26, 2026

GPT-6 Luna

GPT-6 Luna is OpenAI's cheapest current model at $0.10/$0.50 — the direct successor to GPT-5.6 Luna at half the price, with the full 1.05M-token context.

Best for

  • High-volume chat and extraction
  • Classification
  • Cost-capped agent loops

Watch out

Small tier: it matches GPT-5.6 Luna on the Artificial Analysis index but sits well below GPT-6 Sol on hard reasoning; the DeepSWE figure is vendor-reported at max effort.

When the cheaper one wins

GPT-6 Luna is cheaper on output at $0.50 per million tokens against $0.95 for DeepSeek V3.1 — about 1.9×. 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.
  • 4/5 core specs verified on both sides — Not published for at least one side: max output.
  • 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
  • Verified within the last 90 days — Newest catalog check was 2 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 V3.1 · GPT-6 Luna

Common questions

DeepSeek V3.1 vs GPT-6 Luna

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

Is DeepSeek V3.1 or GPT-6 Luna cheaper for input?
GPT-6 Luna is cheaper at $0.10 per million input tokens, against $0.25 for DeepSeek V3.1 — roughly 2.5× 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 V3.1 has tiered pricing: No first-party API: DeepSeek moved the deepseek-chat alias to V3.1-Terminus on 2025-09-22 (the alias itself was retired on 2026-07-24). Third-party hosts listed ~$0.25/$0.95 per MTok (secondary, last checked 2026-08-29) — verify with your host. GPT-6 Luna has tiered pricing: Direct successor to GPT-5.6 Luna at half the price. Cached input $0.01/MTok; cache writes $0.125. Above 272K input the whole request bills $0.20/$0.75 ($0.02 cached). Batch/Flex $0.05/$0.25; Fast mode $0.20/$1.00. Knowledge cutoff May 18 2026.
Is DeepSeek V3.1 or GPT-6 Luna cheaper for output?
GPT-6 Luna is cheaper at $0.50 per million output tokens, against $0.95 for DeepSeek V3.1 — roughly 1.9× 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 V3.1 has tiered pricing: No first-party API: DeepSeek moved the deepseek-chat alias to V3.1-Terminus on 2025-09-22 (the alias itself was retired on 2026-07-24). Third-party hosts listed ~$0.25/$0.95 per MTok (secondary, last checked 2026-08-29) — verify with your host. GPT-6 Luna has tiered pricing: Direct successor to GPT-5.6 Luna at half the price. Cached input $0.01/MTok; cache writes $0.125. Above 272K input the whole request bills $0.20/$0.75 ($0.02 cached). Batch/Flex $0.05/$0.25; Fast mode $0.20/$1.00. Knowledge cutoff May 18 2026.
Which has the larger context window, DeepSeek V3.1 or GPT-6 Luna?
GPT-6 Luna accepts 1.05M tokens against 128K for DeepSeek V3.1. This only matters if you routinely send very long documents or large codebases.
Do DeepSeek V3.1 and GPT-6 Luna support the same reasoning levels?
DeepSeek V3.1 exposes low, high, max, while GPT-6 Luna exposes none, low, medium, high, xhigh, max.
Should I use DeepSeek V3.1 or GPT-6 Luna?
Both sit in the budget tier, so the choice usually comes down to price and context rather than capability. DeepSeek V3.1 suits cost-sensitive hosted agents; GPT-6 Luna suits high-volume chat and extraction.
Can I self-host DeepSeek V3.1 or GPT-6 Luna?
DeepSeek V3.1 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. GPT-6 Luna 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: GPT-6 Luna costs $0.10 per 1M tokens versus $0.25 for DeepSeek V3.1 — a 2.5x difference at the headline tier.
  • Context: GPT-6 Luna takes 1.05M against 128K for DeepSeek V3.1 — only decisive if your prompts approach the smaller window.
  • Deployment: DeepSeek V3.1 publishes weights you can self-host; the other is API-only.
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