TigerBot 70B Chat: Complete Benchmark Performance Guide

other tigerbot-70b-chat 2023-08-22 Apache 2.0

In-depth analysis of TigerBot 70B Chat performance on MMLU, HumanEval, GSM8K, MATH, BBH benchmarks, including pricing and use cases.

Key Specifications

Vendorother
Versiontigerbot-70b-chat
Release Date2023-08-22
Context Window4096 tokens
Input Modalitiestext
Output Modalitiestext
LicenseApache 2.0
Documentationhttps://huggingface.co/models

Benchmark Performance

BenchmarkScoreUnitEvaluated AtNotesSource
MMLU71.7%2023-08-225-shotview
HUMANEVAL36pass@12023-08-22—view
GSM8K51.1%2023-08-220-shot CoTview
MATH15.4%2023-08-220-shot CoTview
BBH51.9%2023-08-223-shot CoTview
GPQA31.2%2023-08-220-shotview
IFEVAL55.7%2023-08-22prompt_strictview
ARC87.9%2023-08-22challengeview
MUSR39.3%2023-08-220-shotview
WINOGRANDE66.3%2023-08-220-shotview

Pricing

TierPriceCurrency
Input$0.9 / MtokUSD
Output$0.9 / MtokUSD
Cache Read$0 / MtokUSD
Cache Write$0 / MtokUSD

Source: https://huggingface.co/models · as of 2023-08-22

Compliance

  • Data Residency: self-host
  • SOC2: ✗
  • HIPAA: ✗
  • GDPR: ✗
  • ISO 27001: ✗

TigerBot 70B Chat

Model Overview

TigerLab TigerBot 70B Chat 中文对话模型, 4K 上下文, 基于 Llama 2 微调, 中文场景优化。

Core Specifications

VendorVersionRelease DateContext WindowInput ModalitiesOutput ModalitiesLicense
Othertigerbot-70b-chat2023-08-224KtexttextApache 2.0

Benchmark Performance

BenchmarkScoreUnitNotes
MMLU (Massive Multitask Language Understanding)71.7%5-shot
HumanEval36.0pass@1—
GSM8K (Grade School Math 8K)51.1%0-shot CoT
MATH15.4%0-shot CoT
BBH (BIG-Bench Hard)51.9%3-shot CoT
GPQA31.2%0-shot
IFEval55.7%prompt_strict
ARC87.9%challenge
MUSR39.3%0-shot
WinoGrande66.3%0-shot

Pricing

InputOutputCache ReadCache Write
————

per million tokens

Strengths

  • Reliable general-purpose model.

Weaknesses

  • HumanEval 36.0, coding weak.
  • Proprietary, not self-hostable.
  • Context window 4K is limited.

Use Cases

  • General chat and Q&A

References