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QwenQwen3.8 27B

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Qwen3.8-27B is an open-weight vision-language model published by Qwen.

Token context
262K tokens
Inputs
Text, Image
Outputs
Text
Released
Not reported

Benchmark Market Position

Intelligence, Cost, and Efficiency

All rankings →

Intelligence

Rank #23 of 57

  1. 100.0*Claude Opus 5.5
  2. 99.0Claude Fable 5.1
  3. 90.9*GPT-5.5 Pro
  4. 90.0Gemini 3.8 Flash
  5. 85.9GPT-6.1 Sol
  6. 84.6GPT-6 Astra
  7. 83.4*Qwen3.8 Max
  8. 83.3*DeepSeek V4.1 Flash
  9. 82.1Gemini 3.1 Pro
  10. 77.3GPT-5.6 Terra
  11. 74.0*Grok 4.7
  12. 73.5*ERNIE 5.1
  13. 73.3Kimi K3
  14. 71.9*GLM 5.3
  15. 67.5*Qwen3.8 Flash
  16. 64.3*Grok 4.20 Multi Agent
  17. 63.3*Qwen3.7 Plus
  18. 63.1*Claude Sonnet 5
  19. 57.9*DeepSeek V4 Pro
  20. 56.2*GLM 5.3 Flash
  21. 54.6*Mistral Large 4
  22. 54.3*Gemma 4 31B
  23. 52.2Qwen3.8 27B
  24. 50.5*Qwen3.5 397B A17B
  25. 50.1*Hy3
  26. 47.4*Gemma 4 26B A4B
  27. 47.4Inkling
  28. 43.0*Mistral Large 3
  29. 42.3GPT-6 Luna
  30. 37.8*NVIDIA Nemotron 3 Ultra 550B A55B BF16
  31. 35.2*Inkling Small
  32. 33.9*MiniMax M3
  33. 27.0*Kimi K2.7 Code
  34. 25.1*Grok Build 0.1
  35. 20.8GPT-5.4 Mini
  36. 17.8Gemini 3.5 Flash Lite
  37. 17.2*Qwen3.5 35B A3B
  38. 15.7GPT-5.4 Nano
  39. 12.8*Muse Glimmer 30B
  40. 11.7*Solar Pro 4
  41. 9.3*Claude Haiku 4.5
  42. 0.4*DeepSeek R1
  43. 0.0*Olmo 3 32B Think
  44. 0.0*Nova 2 Lite
  45. 0.0*Command A
  46. 0.0*Granite 4.2 30B
  47. 0.0*Granite 4.2 3B
  48. 0.0*Granite 4.2 8B
  49. 0.0*Llama 4 Maverick 17B 128E Instruct
  50. 0.0*Llama 4 Scout 17B 16E Instruct
  51. 0.0*phi-4
  52. 0.0*NVIDIA Nemotron 3 Nano 30B A3B BF16
  53. 0.0*NVIDIA Nemotron 3.5 Lightning 30B A3B
  54. 0.0*GPT-4o
  55. 0.0*GPT-4o Mini
  56. 0.0*gpt-oss-120b
  57. 0.0*gpt-oss-20b
* Provisional: fewer than 3 sources
View full ranking →

Cost

Rank #12 of 27

  1. $0.0020Grok Build 0.1
  2. $0.0087GLM 5.3 Flash
  3. $0.017MiniMax M3
  4. $0.018GPT-6 Luna
  5. $0.021Qwen3.8 Flash
  6. $0.022DeepSeek V4.1 Flash
  7. $0.029Gemini 3.5 Flash Lite
  8. $0.044Kimi K2.7 Code
  9. $0.054Mistral Large 4
  10. $0.054DeepSeek V4 Pro
  11. $0.058GPT-5.4 Nano
  12. $0.063Qwen3.8 27B
  13. $0.090Inkling
  14. $0.092NVIDIA Nemotron 3 Ultra 550B A55B BF16
  15. $0.104GPT-6.1 Sol
  16. $0.107Qwen3.8 Max
  17. $0.160Gemini 3.8 Flash
  18. $0.161Gemini 3.1 Pro
  19. $0.163Kimi K3
  20. $0.194Claude Sonnet 5
  21. $0.214GPT-5.4 Mini
  22. $0.248GLM 5.3
  23. $0.266GPT-5.6 Terra
  24. $0.341Grok 4.7
  25. $0.512Claude Opus 5.5
  26. $0.520GPT-6 Astra
  27. $0.824Claude Fable 5.1
View full ranking →

Efficiency

Rank #17 of 27

  1. 71.7*DeepSeek V4.1 Flash
  2. 65.8*GLM 5.3 Flash
  3. 64.2*Qwen3.8 Flash
  4. 62.5*Grok Build 0.1
  5. 60.1GPT-6.1 Sol
  6. 58.6*Qwen3.8 Max
  7. 58.5Gemini 3.8 Flash
  8. 54.6Gemini 3.1 Pro
  9. 53.9*Claude Opus 5.5
  10. 52.8GPT-6 Luna
  11. 51.5*DeepSeek V4 Pro
  12. 50.1Kimi K3
  13. 49.9*Mistral Large 4
  14. 49.5Claude Fable 5.1
  15. 49.0*MiniMax M3
  16. 48.0GPT-5.6 Terra
  17. 47.3Qwen3.8 27B
  18. 46.1GPT-6 Astra
  19. 45.9*GLM 5.3
  20. 44.3*Grok 4.7
  21. 43.5*Claude Sonnet 5
  22. 42.0Inkling
  23. 37.8*Kimi K2.7 Code
  24. 37.1*NVIDIA Nemotron 3 Ultra 550B A55B BF16
  25. 36.6Gemini 3.5 Flash Lite
  26. 29.9GPT-5.4 Nano
  27. 21.6GPT-5.4 Mini
* Provisional: fewer than 3 sources
View full ranking →

The orange outline marks Qwen3.8 27B. Each available panel preserves its real rank and value; missing benchmark or pricing inputs remain explicitly unranked.

Providers & Pricing

Estimate workload cost →
ProviderInput / 1MOutput / 1MCache read / 1MCache write / 1MObservedEvidence
$0.20$2.50$0.050—Oct 19, 2026Provider-reported
$0.24$2.20$0.050—Oct 19, 2026Provider-reported

Benchmarks

All benchmark results →
ARC-AGI-1verified-v1-613c385b0c9387.50percent——Qwen3.8-27B (XHigh)unknownOriginal sourcewinner eligibleThird-party benchmark
ARC-AGI-2verified-v2-be40992860f942.36percent——Qwen3.8-27B (XHigh)unknownOriginal sourcewinner eligibleThird-party benchmark
LiveBench2026-06-25-90f8d44da96578.02percent28,7401,270qwen3.8-27baverage per caseRecomputedwinner eligibleThird-party benchmark
LMArena Text Arenatext-2026-10-15-a64ca3b12b6e1,440.55rating—23,294qwen3.8-27b; 95% CI [1435.47949951, 1445.61514077]; votes 23294; rank 75unknownOriginal sourcewinner eligibleThird-party benchmark
LMArena Vision Arenavision-2026-10-09-a64ca3b12b6e1,271.39rating—7,013qwen3.8-27b; 95% CI [1262.99100972, 1279.79432635]; votes 7013; rank 42unknownOriginal sourcewinner eligibleThird-party benchmark

At a Glance

Model Facts

Identity

Status
active
Developer ID
Qwen/Qwen3.8-27B
Released
Not reported
Version
Qwen3.8-27B
License
apache-2.0

Capacity

Token context
262K tokens
Maximum output
131K tokens
Total parameters
27.8B
Active parameters
Unknown
Knowledge cutoff
Not reported

Interface and Access

Inputs
Text, Image
Outputs
Text
API available
Yes
Open weights
Yes
Self-hostable
Yes
Reasoning
Yes
Vision
Yes
Tool calling
Yes
Capabilities
chat, generation, reasoning, tools

This page represents one developer model product. Dated API snapshots, serving endpoints, pricing, regions, quantizations, and service tiers attach as versioned aliases or provider details and never create duplicate public model records.

Version Lineage

PredecessorUnknown
SuccessorsUnknown
AliasesQwen/Qwen3.8-27B, Qwen/Qwen3.8-27B

Explicit Unknowns

  • Release date
  • Knowledge cutoff

Primary Evidence

Sources and Observation Date

Qwen/Qwen3.8-27B developer model repositoryQwen · observed Aug 28, 2026Deepinfra catalogDeepinfra · observed Oct 19, 2026OpenRouter qwen/qwen3.8-27b model APIOpenRouter · observed Aug 28, 2026Qwen/Qwen3.8-27B Hugging Face inference-provider mappingHugging Face · observed Aug 28, 2026Qwen/Qwen3.8-27B config.json at 1d4bf0f2ff60Qwen · observed Aug 28, 2026Qwen/Qwen3.8-27B README.md at 1d4bf0f2ff60Qwen · observed Aug 28, 2026Qwen/Qwen3.8-27B immutable Hub API metadataQwen · observed Aug 28, 2026Qwen/Qwen3.8-27B tokenizer_config.json at 1d4bf0f2ff60Qwen · observed Aug 28, 2026Hugging Face catalogHugging Face · observed Sep 2, 2026Openrouter catalogOpenrouter · observed Oct 19, 2026

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Questions

Qwen3.8 27B FAQs

What is Qwen3.8 27B?+

Qwen3.8-27B is an open-weight vision-language model published by Qwen. It is developed by Qwen and its current sourced lifecycle status is active.

What inputs and outputs does Qwen3.8 27B support?+

Qwen3.8 27B's current record lists Text and Image as input and Text as output.

How much context does Qwen3.8 27B support?+

The current record lists a 262K-token context window and a maximum output of 131K tokens.

Is Qwen3.8 27B available through an API?+

Qwen3.8 27B is marked as API-available. The directly sourced provider records currently include Deepinfra, Hugging Face, and Openrouter.

How large is Qwen3.8 27B?+

The current record lists 27.8B total parameters and an unknown active parameter count. Its architecture is Qwen3_5ForConditionalGeneration.

What capabilities and tasks does Qwen3.8 27B support?+

Qwen3.8 27B's recorded capabilities are chat, generation, reasoning, and tools. Its supported tasks are image and text.

How much does Qwen3.8 27B cost through an API?+

The lowest directly sourced prices currently attached to Qwen3.8 27B are $0.20 per million input tokens through Deepinfra and $2.20 per million output tokens through Openrouter. Prices are provider-specific and should be checked against each cited observation date.

Can Qwen3.8 27B be self-hosted?+

Qwen3.8 27B is an open-weight model. Self-hosting is supported, and the recorded license is apache-2.0.

Does Qwen3.8 27B have related versions or aliases?+

No predecessor is recorded. No successor is recorded. Recorded aliases are Qwen/Qwen3.8-27B.

Which models can Qwen3.8 27B be compared with?+

The current compatible peer set includes Granite 4.2 30B, Qwen3.8 2.4T A95B, DeepSeek V4 Flash Vision Exp, Ministral 3 14B Base 2512, and Ministral 3 14B Instruct 2512. Compatibility requires shared sourced modalities and tasks; it does not imply that one model is better. Browse model comparisons →

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