Key Specifications

Vendoralibaba
Version1.5-110b
Release Date2024-02-25
Context Window32768 tokens
Input Modalitiestext
Output Modalitiestext
LicenseQwen License
Documentationhttps://qwenlm.github.io/

Benchmark Performance

BenchmarkScoreUnitEvaluated AtNotesSource
MMLU86.1%2024-02-255-shotview
HUMANEVAL76.5pass@12024-02-25view
GSM8K80.6%2024-02-250-shot CoTview
MATH54.1%2024-02-250-shot CoTview
BBH82.3%2024-02-253-shot CoTview
GPQA45.9%2024-02-250-shotview
IFEVAL83.4%2024-02-25prompt_strictview
ARC95.7%2024-02-25challengeview
MUSR63.9%2024-02-250-shotview
WINOGRANDE84%2024-02-250-shotview

Pricing

TierPriceCurrency
Input$0.7 / MtokUSD
Output$1.2 / MtokUSD
Cache Read$0 / MtokUSD
Cache Write$0 / MtokUSD

Source: https://help.aliyun.com/zh/model-studio/getting-started/models · as of 2024-02-25

Compliance

  • Data Residency: CN
  • SOC2: ✗
  • HIPAA: ✗
  • GDPR: ✗
  • ISO 27001: ✗

Qwen1.5 110B

Aperçu du modèle

阿里巴巴 Qwen1.5 110B 开源超大模型, 32K 上下文, 在中文与多语言基准上表现突出。

Spécifications principales

FournisseurVersionDate de sortieFenêtre de contexteModalités d’entréeModalités de sortieLicence
Alibaba1.5-110b2024-02-2532KtexttextQwen License

Performance aux benchmarks

BenchmarkScoreUnitéNotes
MMLU (Massive Multitask Language Understanding)86.1%5-shot
HumanEval76.5pass@1
GSM8K (Grade School Math 8K)80.6%0-shot CoT
MATH54.1%0-shot CoT
BBH (BIG-Bench Hard)82.3%3-shot CoT
GPQA45.9%0-shot
IFEval83.4%prompt_strict
ARC95.7%challenge
MUSR63.9%0-shot
WinoGrande84.0%0-shot

Tarification

EntréeSortieLecture cacheÉcriture cache

par million de jetons

Forces

  • MMLU score 86.1, strong knowledge reasoning.

Faiblesses

  • 闭源专有模型,不支持自托管。

Cas d’usage

  • 代码生成与调试

Références