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Van Data Team

text model comparison

DeepSeek-V4.1-Flash vs GPT-6 Luna

DeepSeek-V4.1-Flash and GPT-6 Luna are both current text models, from DeepSeek and OpenAI. GPT-6 Luna is 67% cheaper per 1M input tokens than DeepSeek-V4.1-Flash, $0.10 vs $0.30. On Arena Text, DeepSeek-V4.1-Flash scores 1476 Elo and GPT-6 Luna 1441 Elo (Arena, measured October 28, 2026). GPT-6 Luna has the larger context window, 1,050,000 vs 1,000,000 tokens.

Higher Arena Text
DeepSeek-V4.1-Flash1476 Elo against 1441 Elo
Lower price per 1M input tokens
GPT-6 Luna$0.10 against $0.30
Longer context window
GPT-6 Luna1.05M tokens against 1M tokens
Newer release
GPT-6 LunaSep 22, 2026 against Sep 10, 2026

Data verified November 3, 2026 · Dataset 2026-11-03

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Side by side

DeepSeek-V4.1-Flash and GPT-6 Luna, line by line

Prices in effect today, compared at the same tier wherever both list one. The better value in each row is highlighted.

FactDeepSeek-V4.1-FlashGPT-6 Luna
Price
Price per 1M input tokens$0.30$0.10 (better)
Price per 1M output tokens$1.20$0.50 (better)
Independent benchmarks
Arena Text1476 Elo (#21 of 51) (better)1441 Elo (#37 of 51)
Arena WebDev1665 Elo (#12 of 45) (better)1579 Elo (#28 of 45)
FrontierMath Tiers 1-3 (v2)71.2% (#23 of 42)78.9% (#17 of 42) (better)
GPQA Diamond93.2% (#16 of 41) (better)90.5% (#26 of 41)
SimpleQA Verified42.5% (#27 of 38) (better)41.4% (#28 of 38)
Specs
ProviderDeepSeekOpenAI
Release dateSeptember 10, 2026September 22, 2026
AccessAPI and open weightsAPI only
Context window1,000,000 tokens1,050,000 tokens
Max output384,000 tokens128,000 tokens
Inputtext, imagetext, image
Outputtexttext

Scores:Arena · 2026-11-03Epoch AI · 2026-11-03

Open both in the interactive comparison

Charts

Against every current text model

Where DeepSeek-V4.1-Flash and GPT-6 Luna land among the current models of their task, on every independent benchmark, on price and on context.

Where each stands

On Arena Text, DeepSeek-V4.1-Flash ranks #21 and GPT-6 Luna #37 of 51 current models. Each bar is the share of current models it beats: on score, price and context.

DeepSeek-V4.1-Flash and GPT-6 Luna among the current text models, one row per benchmark, price and context window.

Independent benchmarks

Arena Text

DeepSeek-V4.1-Flash:#21of 51

1,476 Elo · ahead of 58%

GPT-6 Luna:#37of 51

1,441 Elo · ahead of 26%

Arena WebDev

DeepSeek-V4.1-Flash:#12of 45

1,665 Elo · ahead of 75%

GPT-6 Luna:#28of 45

1,579 Elo · ahead of 39%

FrontierMath Tiers 1-3 (v2)

DeepSeek-V4.1-Flash:#23of 42

71.2% · ahead of 46%

GPT-6 Luna:#17of 42

78.9% · ahead of 61%

GPQA Diamond

DeepSeek-V4.1-Flash:#16of 41

93.2% · ahead of 63%

GPT-6 Luna:#26of 41

90.5% · ahead of 35%

SimpleQA Verified

DeepSeek-V4.1-Flash:#27of 38

42.5% · ahead of 30%

GPT-6 Luna:#28of 38

41.4% · ahead of 27%

Price and context

Price per 1M input tokens

DeepSeek-V4.1-Flash:#11of 52

$0.30 · cheaper than 75%

GPT-6 Luna:#1of 52

$0.10 · cheaper than 96%

Price per 1M output tokens

DeepSeek-V4.1-Flash:#10of 52

$1.20 · cheaper than 76%

GPT-6 Luna:#3of 52

$0.50 · cheaper than 92%

Context window

DeepSeek-V4.1-Flash:#26of 64

1M tokens · longer than 22%

GPT-6 Luna:#1of 64

1.05M tokens · longer than 86%

Scores fromArena · 2026-11-03Epoch AI · 2026-11-03

Quality against price

Arena Text · measured October 28, 2026

DeepSeek-V4.1-Flash scores 1,476 at $0.525; GPT-6 Luna scores 1,441 at $0.2 (blended price per 1M tokens). The line joins the current models no other beats on both price and Arena Text score; hover any point to name it.

Quality against priceArena Text score against price for 43 text models, DeepSeek-V4.1-Flash and GPT-6 Luna marked.1,2501,3001,3501,4001,4501,5001,550$0.30$1$3$10MOST ATTRACTIVE QUADRANTMedian price $3Median 1,475Blended price per 1M tokens (3 input : 1 output), log scaleArena Text (Elo)DeepSeek-V4.1-FlashGPT-6 Luna
Quality against price: the data
Arena Text score against price for 43 text models, DeepSeek-V4.1-Flash and GPT-6 Luna marked.
ModelProviderBlended price per 1M tokensArena Text (Elo)
Gemini 4 ArgonGoogle$41,520
Claude Opus 5.5Anthropic$81,509
Muse WonderMeta$81,507
Claude Fable 5Anthropic$201,504
Claude Fable 5.1Anthropic$201,504
Gemini 3.8 FlashGoogle$1.501,496
Muse Spark 1.3Meta$21,495
Claude Opus 5Anthropic$101,492
Kimi K3Moonshot Kimi$61,488
GPT-5.6 SolOpenAI$81,485
Gemini 3.6 FlashGoogle$31,483
GPT-5.5OpenAI$111,482
Claude Opus 4.8Anthropic$101,482
Qwen3.8-MaxAlibaba Qwen$31,482
GPT-6.1 SolOpenAI$41,481
GLM-5.3Z.ai$2.151,481
MiMo-V2.6-ProXiaomi MiMo$0.541,480
Claude Sonnet 5.5Anthropic$41,477
GLM-5.3-FlashZ.ai$0.241,477
GPT-6 AstraOpenAI$201,476
DeepSeek-V4.1-FlashDeepSeek$0.521,476
GPT-5.4OpenAI$5.631,475
Gemini 3 Flash PreviewGoogle$1.131,473
Grok 4.20xAI$1.561,472
GPT-5.6 TerraOpenAI$4.501,467
Grok 4.5xAI$31,465
DeepSeek-V4-ProDeepSeek$1.981,465
Claude Sonnet 5Anthropic$41,462
GPT-6 SolOpenAI$41,458
Gemini 3.5 Flash-LiteGoogle$0.851,456
Grok 4.6xAI$31,455
GPT-5.6 LunaOpenAI$0.451,453
MiMo-V2.6-FlashXiaomi MiMo$0.181,448
Step 5 PreviewStepFun$1.431,448
Grok 4.3xAI$1.561,442
GPT-6 LunaOpenAI$0.201,441
Grok 4.7xAI$31,441
Mistral Large 4Mistral AI$1.051,432
Claude Haiku 5.5Anthropic$0.201,425
GPT-4.1OpenAI$3.501,415
Solar Pro 4Upstage$0.521,388
GPT-4.1 miniOpenAI$0.701,383
GPT-4.1 nanoOpenAI$0.181,322

Cost

What each costs

Example workloads at each provider's listed rates, then every other rate either one lists. The cheaper figure in each row is highlighted.

The same work, priced

For 10M input and 2M output tokens, DeepSeek-V4.1-Flash costs 2.7 times as much as GPT-6 Luna, at each provider's listed rates.

What DeepSeek-V4.1-Flash and GPT-6 Luna cost for the same work, at the rates each provider lists.

  • 10M input and 2M output tokens

    DeepSeek-V4.1-Flash costs 2.7× as much

    DeepSeek-V4.1-Flash
    $5.40
    GPT-6 Luna
    $2

  • The same, with 9M of the input tokens cached

    DeepSeek-V4.1-Flash costs 2.3× as much

    DeepSeek-V4.1-Flash
    $2.75
    GPT-6 Luna
    $1.19
Workload or rateDeepSeek-V4.1-FlashGPT-6 Luna
Example workloads
10M input and 2M output tokens$5.40$2 (better)
The same, with 9M of the input tokens cached$2.75$1.19 (better)
Other listed rates
1M input tokens, cached$0.006 (better)$0.01
1M input tokens, prompts over 272K tokensNot listed$0.20
1M output tokens, prompts over 272K tokensNot listed$0.75
1M input tokens, off peak$0.15Not listed
1M output tokens, off peak$0.60Not listed
1M input tokens, off-peak, cached$0.003Not listed

Your own bill will differ. These figures use list prices and example workloads. The AI Model Cost Audit reviews your real usage, shortlists models that score as well for each task for less, and estimates the savings.

Launch price $100, regular price $150

Book the cost audit

Verdict

When to choose each

DeepSeek-V4.1-Flash

Where it leads

  • Higher Arena Text score, 1476 Elo vs 1441 Elo
  • Higher Arena WebDev score, 1665 Elo vs 1579 Elo
  • Higher GPQA Diamond score, 93.2% vs 90.5%
  • Higher SimpleQA Verified score, 42.5% vs 41.4%
  • Longer responses, up to 384,000 vs 128,000 output tokens
  • Open weights you can run yourself
  • Cheaper cached input, $0.006 vs $0.01 per 1M tokens

Best for

  • High-volume agent and multimodal workloads where per-token cost dominates
  • Teams that want a frontier-adjacent model they can also self-host under MIT terms

Watch out for

  • The recorded API rates are the peak-hour prices; DeepSeek charges half outside 01:00-04:00 and 06:00-10:00 UTC on weekdays
  • Running the open weights moves cost to your own infrastructure, which the token rates here do not represent
  • Epoch AI and Arena WebDev scored build 1017, which the API serves; Arena Text has rated only the September build so far
Full DeepSeek-V4.1-Flash profile

GPT-6 Luna

Where it leads

  • Lower input and output prices, $0.10 and $0.50 vs $0.30 and $1.20 per 1M tokens
  • Higher FrontierMath Tiers 1-3 (v2) score, 78.9% vs 71.2%
  • Larger context window 1,050,000 vs 1,000,000 tokens

Best for

  • High-volume summarisation, extraction and routing
  • Long-context budget work, where the 272k threshold is more forgiving than Haiku 5.5's 100k

Watch out for

  • Prompts over 272,000 tokens are rebilled at $0.20 input and $0.75 output for the whole request
  • A twentieth of GPT-6 Sol's price reflects a capability gap, not a discount on the same model
Full GPT-6 Luna profile

From benchmark to production

Building on DeepSeek-V4.1-Flash or GPT-6 Luna?

Public scores rarely hold on your own data. We test both models on your real tasks, then build the agent or pipeline around the one that wins.

AI Model Cost AuditLaunch price $100, regular price $150What the audit includes

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FAQ

DeepSeek-V4.1-Flash vs GPT-6 Luna FAQ

Which is cheaper, DeepSeek-V4.1-Flash or GPT-6 Luna?

GPT-6 Luna is 67% cheaper per 1M input tokens than DeepSeek-V4.1-Flash, $0.10 vs $0.30. For 10M input and 2M output tokens, DeepSeek-V4.1-Flash costs $5.40 and GPT-6 Luna $2 at standard rates.

Which is cheaper with prompt caching, DeepSeek-V4.1-Flash or GPT-6 Luna?

DeepSeek-V4.1-Flash charges $0.006 per 1M cached input tokens, 98% below its standard input rate, and GPT-6 Luna $0.01, 90% below. With 9M of 10M input tokens cached and 2M output tokens, DeepSeek-V4.1-Flash costs $2.75 and GPT-6 Luna $1.19.

Which scores higher on independent benchmarks, DeepSeek-V4.1-Flash or GPT-6 Luna?

DeepSeek-V4.1-Flash leads on Arena Text, 1476 Elo to 1441 Elo; DeepSeek-V4.1-Flash leads on Arena WebDev, 1665 Elo to 1579 Elo; GPT-6 Luna leads on FrontierMath Tiers 1-3 (v2), 78.9% to 71.2%. Scores are independent evaluations, not either vendor's launch figures.

Which has the larger context window, DeepSeek-V4.1-Flash or GPT-6 Luna?

GPT-6 Luna has the larger context window, 1,050,000 vs 1,000,000 tokens. DeepSeek-V4.1-Flash returns up to 384,000 tokens per response, GPT-6 Luna 128,000.

Can I run DeepSeek-V4.1-Flash or GPT-6 Luna myself?

DeepSeek-V4.1-Flash is released as open weights you can run yourself; GPT-6 Luna is available through its provider's API only.

Further reading

More on DeepSeek-V4.1-Flash and GPT-6 Luna

Articles on DeepSeek-V4.1-Flash and GPT-6 Luna

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Production evaluation

Choosing between DeepSeek-V4.1-Flash and GPT-6 Luna?

Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.

  • A head-to-head evaluation on your real workload
  • Routing between models by cost and difficulty
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