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Van Data Team

text model comparison

DeepSeek-V4.1-Flash vs Qwen3.8-Max

DeepSeek-V4.1-Flash and Qwen3.8-Max are both current text models, from DeepSeek and Alibaba Qwen. DeepSeek-V4.1-Flash is 85% cheaper per 1M input tokens than Qwen3.8-Max, $0.30 vs $2. On Arena Text, DeepSeek-V4.1-Flash scores 1476 Elo and Qwen3.8-Max 1482 Elo (Arena, measured October 28, 2026). Both accept 1,000,000 tokens of context.

Higher Arena Text
Qwen3.8-Max1482 Elo against 1476 Elo
Lower price per 1M input tokens
DeepSeek-V4.1-Flash$0.30 against $2
Newer release
DeepSeek-V4.1-FlashSep 2026 against Aug 2026

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

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Side by side

DeepSeek-V4.1-Flash and Qwen3.8-Max, 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-FlashQwen3.8-Max
Price
Price per 1M input tokens$0.30 (better)$2
Price per 1M output tokens$1.20 (better)$6
Independent benchmarks
Arena Text1476 Elo (#21 of 51)1482 Elo (#13 of 51) (better)
Arena WebDev1665 Elo (#12 of 45)1672 Elo (#11 of 45) (better)
FrontierMath Tiers 1-3 (v2)71.2% (#23 of 42)74.7% (#20 of 42) (better)
GPQA Diamond93.2% (#16 of 41) (better)92.7% (#18 of 41)
SimpleQA Verified42.5% (#27 of 38)45.8% (#24 of 38) (better)
Specs
ProviderDeepSeekAlibaba Qwen
Release dateSeptember 10, 2026August 2, 2026
AccessAPI and open weightsAPI only
Context window1,000,000 tokens1,000,000 tokens
Max output384,000 tokens131,072 tokens
Inputtext, imagetext, image, video
Outputtexttext

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

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Charts

Against every current text model

Where DeepSeek-V4.1-Flash and Qwen3.8-Max 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 Qwen3.8-Max #13 of 51 current models. Each bar is the share of current models it beats: on score, price and context.

DeepSeek-V4.1-Flash and Qwen3.8-Max 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%

Qwen3.8-Max:#13of 51

1,482 Elo · ahead of 72%

Arena WebDev

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

1,665 Elo · ahead of 75%

Qwen3.8-Max:#11of 45

1,672 Elo · ahead of 77%

FrontierMath Tiers 1-3 (v2)

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

71.2% · ahead of 46%

Qwen3.8-Max:#20of 42

74.7% · ahead of 54%

GPQA Diamond

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

93.2% · ahead of 63%

Qwen3.8-Max:#18of 41

92.7% · ahead of 55%

SimpleQA Verified

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

42.5% · ahead of 30%

Qwen3.8-Max:#24of 38

45.8% · ahead of 38%

Price and context

Price per 1M input tokens

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

$0.30 · cheaper than 75%

Qwen3.8-Max:#29of 52

$2 · cheaper than 24%

Price per 1M output tokens

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

$1.20 · cheaper than 76%

Qwen3.8-Max:#28of 52

$6 · cheaper than 41%

Context window

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

1M tokens · longer than 22%

Qwen3.8-Max:#26of 64

1M tokens · longer than 22%

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; Qwen3.8-Max scores 1,482 at $3 (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 Qwen3.8-Max 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)Qwen3.8-MaxDeepSeek-V4.1-Flash
Quality against price: the data
Arena Text score against price for 43 text models, DeepSeek-V4.1-Flash and Qwen3.8-Max 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, Qwen3.8-Max costs 5.9 times as much as DeepSeek-V4.1-Flash, at each provider's listed rates.

What DeepSeek-V4.1-Flash and Qwen3.8-Max cost for the same work, at the rates each provider lists.

  • 10M input and 2M output tokens

    Qwen3.8-Max costs 5.9× as much

    DeepSeek-V4.1-Flash
    $5.40
    Qwen3.8-Max
    $32
Workload or rateDeepSeek-V4.1-FlashQwen3.8-Max
Example workloads
10M input and 2M output tokens$5.40 (better)$32
The same, with 9M of the input tokens cached$2.75Not listed
Other listed rates
1M input tokens, cached$0.006Not listed
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

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Verdict

When to choose each

DeepSeek-V4.1-Flash

Where it leads

  • Lower input and output prices, $0.30 and $1.20 vs $2 and $6 per 1M tokens
  • Higher GPQA Diamond score, 93.2% vs 92.7%
  • Longer responses, up to 384,000 vs 131,072 output tokens
  • Open weights you can run yourself
  • A cached-input rate, $0.006 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

Qwen3.8-Max

Where it leads

  • Higher Arena Text score, 1482 Elo vs 1476 Elo
  • Higher Arena WebDev score, 1672 Elo vs 1665 Elo
  • Higher FrontierMath Tiers 1-3 (v2) score, 74.7% vs 71.2%
  • Higher SimpleQA Verified score, 45.8% vs 42.5%
  • Accepts video input

Best for

  • Output-heavy generation workloads where the $6 per million output rate is the deciding factor
  • Agentic and coding evaluations that need a 1M-token window at mid-tier cost

Watch out for

  • Two releases share the name: the original 2 August 2026 model and the 0902 refresh, a separate id at the same price
  • The recorded rates are the international (Singapore) price; the Global and Beijing listings charge $1.65 input and $4.951 output per 1M tokens
  • Alibaba publishes no fixed cached-input rate for it
Full Qwen3.8-Max profile

From benchmark to production

Building on DeepSeek-V4.1-Flash or Qwen3.8-Max?

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 Qwen3.8-Max FAQ

Which is cheaper, DeepSeek-V4.1-Flash or Qwen3.8-Max?

DeepSeek-V4.1-Flash is 85% cheaper per 1M input tokens than Qwen3.8-Max, $0.30 vs $2. For 10M input and 2M output tokens, DeepSeek-V4.1-Flash costs $5.40 and Qwen3.8-Max $32 at standard rates.

Do DeepSeek-V4.1-Flash and Qwen3.8-Max discount cached input?

DeepSeek-V4.1-Flash lists a cached-input rate of $0.006 per 1M tokens, 98% below its standard input rate. No cached-input rate is listed for Qwen3.8-Max.

Which scores higher on independent benchmarks, DeepSeek-V4.1-Flash or Qwen3.8-Max?

Qwen3.8-Max leads on Arena Text, 1482 Elo to 1476 Elo; Qwen3.8-Max leads on Arena WebDev, 1672 Elo to 1665 Elo; Qwen3.8-Max leads on FrontierMath Tiers 1-3 (v2), 74.7% to 71.2%. Scores are independent evaluations, not either vendor's launch figures.

Which has the larger context window, DeepSeek-V4.1-Flash or Qwen3.8-Max?

Both accept 1,000,000 tokens of context. DeepSeek-V4.1-Flash returns up to 384,000 tokens per response, Qwen3.8-Max 131,072.

How do DeepSeek-V4.1-Flash and Qwen3.8-Max differ in features?

DeepSeek-V4.1-Flash takes text and image input; Qwen3.8-Max takes text, image and video.

Can I run DeepSeek-V4.1-Flash or Qwen3.8-Max myself?

DeepSeek-V4.1-Flash is released as open weights you can run yourself; Qwen3.8-Max is available through its provider's API only.

Further reading

More on DeepSeek-V4.1-Flash and Qwen3.8-Max

Articles on DeepSeek-V4.1-Flash and Qwen3.8-Max

Related comparisons

Production evaluation

Choosing between DeepSeek-V4.1-Flash and Qwen3.8-Max?

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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