GLM / Z.ai (Zhipu AI) vs Cohere Transcribe

Which one should you pick? Here's the full breakdown.

Our Pick

GLM / Z.ai (Zhipu AI)

A
8.0/10

Zhipu AI's open-weights family -- GLM-5.1 (launched 2026-04-07) is 744B MoE / 40B active, topped SWE-Bench Pro at 58.4 (beating GPT-5.4 and Claude Opus 4.6), MIT licensed, 200K context. Trained entirely on 100K Huawei Ascend 910B chips -- first frontier model with zero Nvidia in the training stack

Cohere Transcribe

A
8.0/10

Cohere's first audio model -- launched 2026-03-26 under Apache 2.0, 2B parameters, #1 on Hugging Face Open ASR Leaderboard (5.42 avg WER), 14 enterprise-critical languages. Free API with rate limits; Model Vault for production

CategoryGLM / Z.ai (Zhipu AI)Cohere Transcribe
Ease of Use6.57.0
Output Quality8.59.0
Value9.09.0
Features8.07.0
Overall8.08.0

Pricing Comparison

FeatureGLM / Z.ai (Zhipu AI)Cohere Transcribe
Free TierYesYes
Starting Price$0$0

Benchmark Head-to-Head

GLM-5.1 (744B MoE / 40B active) benchmarks — Cohere Transcribe has no published benchmarks

BenchmarkScore
SWE-Bench Pro58.4%
MMLU-Pro81.2%
GPQA Diamond74.5%
HumanEval89.1%
SWE-Bench Verified64.2%
BFCL (function calling)88%

Which Should You Pick?

Pick GLM / Z.ai (Zhipu AI) if...

  • More features (8 vs 7)

Teams that need genuine MIT-licensed frontier open weights with no commercial strings. Especially strong for agentic workflows and vision (GLM-4.6V).

Visit GLM / Z.ai (Zhipu AI)

Pick Cohere Transcribe if...

Enterprise teams transcribing English, European, and major APAC languages at scale who want open weights they can self-host, fine-tune, or deploy on-prem. The Apache 2.0 license removes a major procurement blocker compared to proprietary ASR, and the accuracy tier is now best-in-class for open models.

Visit Cohere Transcribe

Our Verdict

GLM / Z.ai (Zhipu AI) and Cohere Transcribe are extremely close overall. Your choice comes down to specific needs -- GLM / Z.ai (Zhipu AI) is better for teams that need genuine mit-licensed frontier open weights with no commercial strings, while Cohere Transcribe works best for enterprise teams transcribing english, european, and major apac languages at scale who want open weights they can self-host, fine-tune, or deploy on-prem.