Qwen3.8 27B vs DeepSeek V4 Pro

Market Position

LiveBench Quality Versus Estimated Output Cost

Full ranking →
Efficiency FrontierLiveBench overall · output estimate
Upper-left is better
xAIDeepSeekZ.aiMiniMaxOpenAIQwenGoogle DeepMindMoonshot AIAnthropic
LiveBench quality versus score-adjusted output costEach dot is a reviewed major-model configuration and is colored by developer. Higher means a better LiveBench overall score. Farther left means lower estimated output cost after adjusting by the score. A dotted line connects the non-dominated frontier observations. When models are selected, their sourced families remain prominent, unrelated observations retain their developer colors at lower opacity, and an orange ring identifies each selected model.$0.0050$0.010$0.020$0.050$0.100$0.200$0.5006873788287Grok Build 0.1GLM 5.3 FlashGPT-5.6 Luna (max)DeepSeek V4 Flash Vision ExpGPT-5.6 Sol (max)Score-adjusted output cost per LiveBench case (log) →LiveBench overall →
The dotted frontier connects measured, non-dominated major-model observations. With a selection, sourced families stay prominent, unrelated observations retain their developer colors at lower opacity, and orange rings mark the selected model or models. Family lines connect models only when their sourced family and generation match. Cost is estimated from published output tokens and the lowest current USD output rate; it excludes input, caching, batch discounts, and provider-specific benchmark execution details.

This current-market view appears only when both compared models are reviewed current models with publisher-reported LiveBench token accounting and current sourced USD output rates.

Model Markets Rankings

Intelligence, Cost, and Efficiency

All rankings →
RankingQwen3.8-27BDeepSeek-V4-Pro
CostLower is better · Published-token output estimate#16 of 36$0.086 per LiveBench case#9 of 36$0.054 per LiveBench case

Ranks come from the current complete eligible cohorts. Green highlights appear only when both models are ranked in the same metric. Missing required inputs remain unranked, and the three dimensions are not collapsed into an overall winner.

Benchmark Performance

Available Benchmarks

BenchmarkQwen3.8-27BDeepSeek-V4-Pro
LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader1,437.3599% of row best · rating · qwen3.8-27b; 95% CI [1429.71618499, 1444.98971204]; votes 6626; rank 691,451.00100% of row best · rating · deepseek-v4-pro; 95% CI [1447.00829245, 1454.98663953]; votes 54243; rank 41
LiveBench2026-06-25 · overall · leader78.02100% of row best · percent · qwen3.8-27b · 28,740 output tokens / case76.7998% of row best · percent · deepseek-v4-pro · 35,014 output tokens / case
Overall ResultCounted from the protocol-matched rows above1 benchmark winTied overall1 benchmark winTied overall

Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.

FieldAt a Glance
Qwen · activeQwen3.8 27BVerified Aug 28, 2026
DeepSeek · activeDeepSeek V4 ProVerified Aug 28, 2026

Technical Differences

Side-by-Side Facts

Indexable
FieldQwen3.8-27BDeepSeek-V4-Pro
DeveloperQwenDeepSeek
FamilyQwen3 8 27bDeepseek V4 Pro
ModelQwen3.8-27BDeepSeek-V4-Pro
VersionQwen3.8-27BDeepSeek-V4-Pro
Lifecycleactiveactive
ReleasedUnknown2026-04-24
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText
Output modalitiesTextText
Context window262K1,049K
Total parameters27.8B1.6T
Active parametersUnknown49B
Licenseapache-2.0mit
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)DeepSeek (Standard), Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitieschat, generation, reasoning, toolschat, generation, reasoning

15 comparable fields · 10 material differences · Pair passes the primary-source comparison gate

Qwen3.8 27B Capabilities

chatgenerationreasoningtools
Input price$0.40
Output price$3.00
Serving providers3
Canonical IDQwen/Qwen3.8-27B

DeepSeek V4 Pro Capabilities

chatgenerationreasoning
Input price$0.66
Output price$1.5441
Serving providers6
Canonical IDdeepseek-ai/DeepSeek-V4-Pro

Internal Comparison Graph

Related Comparisons

All text comparisons →
APairBContext
vscross-developer peersimage, text
vscross-developer peersimage, text
vscross-developer peerstext
vscross-developer peersimage, text
vsfamily variantsimage, text
vscross-developer peersimage, text
vscross-developer peersimage, text
vscross-developer peerstext
vscross-developer peerstext
vscross-developer peersimage, text
vscross-developer peersimage, text
vscross-developer peersimage, text

Primary Evidence

Sources and Freshness

Questions

Qwen3.8 27B vs DeepSeek V4 Pro FAQs

Is Qwen3.8 27B or DeepSeek V4 Pro better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.8 27B and DeepSeek V4 Pro, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Qwen3.8 27B or DeepSeek V4 Pro?+

Qwen3.8 27B is $0.40 and DeepSeek V4 Pro is $0.66 per million tokens, so Qwen3.8 27B is cheaper on this metric. Qwen3.8 27B is $3.00 and DeepSeek V4 Pro is $1.5441 per million tokens, so DeepSeek V4 Pro is cheaper on this metric.

Which has a larger context window, Qwen3.8 27B or DeepSeek V4 Pro?+

DeepSeek V4 Pro has the larger sourced context window. Qwen3.8 27B supports 262K and DeepSeek V4 Pro supports 1,049K.

Which performs better in benchmarks, Qwen3.8 27B or DeepSeek V4 Pro?+

There is no overall benchmark winner: The verified common benchmarks do not produce a majority winner.

Can Qwen3.8 27B or DeepSeek V4 Pro be self-hosted?+

Both models have the same recorded self-hosting status: supported. Qwen3.8 27B is open weight; DeepSeek V4 Pro is open weight.

Can Qwen3.8 27B and DeepSeek V4 Pro understand images?+

Qwen3.8 27B is documented with image input; DeepSeek V4 Pro is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Qwen3.8 27B or DeepSeek V4 Pro?+

Neither has a larger sourced maximum output. Qwen3.8 27B is 131K and DeepSeek V4 Pro is —.

Do Qwen3.8 27B and DeepSeek V4 Pro support reasoning and tool use?+

Qwen3.8 27B: reasoning, tool calling, and image input. DeepSeek V4 Pro: reasoning. Feature support does not establish relative quality.

Which is available from more inference providers, Qwen3.8 27B or DeepSeek V4 Pro?+

Qwen3.8 27B has 3 sourced provider routes; DeepSeek V4 Pro has 6, so DeepSeek V4 Pro has broader tracked availability.

Which offers better value, Qwen3.8 27B or DeepSeek V4 Pro?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

Send Feedback