GLM / Z.ai (Zhipu AI) vs MiMo (Xiaomi)
Which one should you pick? Here's the full breakdown.
GLM / Z.ai (Zhipu AI)
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
MiMo (Xiaomi)
Xiaomi's MiMo-V2.5 family launched 2026-04-22 -- Pro (1T total / 42B active MoE, 1M context, native vision+audio reasoning), Multimodal base, TTS (3 sub-models: base, VoiceDesign, VoiceClone), and ASR (open-source, English + Chinese + major dialects). Full voice pipeline for the agent era. Extra-charge 1M-context tier removed at launch
| Category | GLM / Z.ai (Zhipu AI) | MiMo (Xiaomi) |
|---|---|---|
| Ease of Use | 6.5 | 7.0 |
| Output Quality | 8.5 | 8.0 |
| Value | 9.0 | 9.0 |
| Features | 8.0 | 9.0 |
| Overall | 8.0 | 8.3 |
Personality & Tone
GLM / Z.ai (Zhipu AI): The Z.ai research model
Tone: Academic and structured. GLM-4.6's instruction-tuned chat tends toward outlined, bullet-heavy responses and leans on established phrasing rather than casual voice.
Quirks: Strong on multilingual and tool use, weaker at playful conversation. Smaller community fine-tuning ecosystem than Llama or Qwen, so fewer 'flavored' checkpoints to pick from -- most deployments run the base instruction-tune.
MiMo (Xiaomi): Xiaomi's voice-first agentic stack
Tone: Direct, multimodal-aware. MiMo-V2.5-Pro is comfortable mixing image, audio, and text inputs in a single turn -- it's been trained for that, not retrofitted to it.
Quirks: Voice-pipeline orientation makes MiMo unusually expressive when audio is in the loop -- TTS variants (VoiceDesign, VoiceClone) and ASR are surfaced as first-class products, which most Chinese frontier vendors haven't done. PRC content filters apply on chat surfaces.
Pricing Comparison
| Feature | GLM / Z.ai (Zhipu AI) | MiMo (Xiaomi) |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Benchmark Head-to-Head
GLM-5.1 (744B MoE / 40B active) benchmarks — MiMo (Xiaomi) has no published benchmarks
| Benchmark | Description | Score |
|---|---|---|
| SWE-Bench Pro | 58.4% | |
| MMLU-Pro | Harder multi-subject reasoning | 81.2% |
| GPQA Diamond | Graduate-level science questions | 74.5% |
| HumanEval | Python code generation | 89.1% |
| SWE-Bench Verified | 64.2% | |
| BFCL (function calling) | 88% |
Which Should You Pick?
Pick GLM / Z.ai (Zhipu AI) if...
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 MiMo (Xiaomi) if...
- ✓More features (9 vs 8)
Teams building voice-first agentic products that need a coordinated reasoning + TTS + ASR stack from a single vendor. Also Chinese-market builders and developers who need strong multimodal (vision + audio) inputs in one API call without stitching three providers together. The no-surcharge 1M-context stance makes MiMo-V2.5-Pro especially attractive for long-document agentic workloads.
Visit MiMo (Xiaomi)Our Verdict
MiMo (Xiaomi) edges out GLM / Z.ai (Zhipu AI) with a 8.3 vs 8.0 overall score. Both are solid picks, but MiMo (Xiaomi) has the advantage in features.