Llama 4 (Meta) vs MiMo (Xiaomi)
Which one should you pick? Here's the full breakdown.
Llama 4 (Meta)
Meta's open-weights flagship family -- Scout (10M context), Maverick (multimodal 400B MoE), Behemoth in preview
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 | Llama 4 (Meta) | MiMo (Xiaomi) |
|---|---|---|
| Ease of Use | 5.0 | 7.0 |
| Output Quality | 8.5 | 8.0 |
| Value | 9.0 | 9.0 |
| Features | 9.0 | 9.0 |
| Overall | 7.9 | 8.3 |
Personality & Tone
Llama 4 (Meta): The open-weight workhorse
Tone: Plain, helpful, and neutral. Meta's instruction-tuned Llama 4 reads like a sanitized ChatGPT -- useful for general tasks but without a strong persona of its own.
Quirks: The 'real' personality depends on the checkpoint you run. Base Llama 4 is bland by design; the interesting behaviors come from community fine-tunes (Nous, Hermes, Dolphin, etc.) that give it different voices and refusal patterns.
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 | Llama 4 (Meta) | MiMo (Xiaomi) |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Benchmark Head-to-Head
Llama 4 Maverick (17B/400B MoE) benchmarks — MiMo (Xiaomi) has no published benchmarks
| Benchmark | Description | Score |
|---|---|---|
| MMLU-Pro | Harder multi-subject reasoning | 80.5% |
| GPQA Diamond | Graduate-level science questions | 69.8% |
| HumanEval | Python code generation | 88% |
| MMMU (multimodal) | 73.4% |
Which Should You Pick?
Pick Llama 4 (Meta) if...
Developers and teams who need a permissively-licensed open-weights model with strong tooling, long context (Scout), or multimodal (Maverick). Safe default choice given the ecosystem.
Visit Llama 4 (Meta)Pick MiMo (Xiaomi) if...
- ✓Easier to use (7 vs 5)
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 Llama 4 (Meta) with a 8.3 vs 7.9 overall score. Both are solid picks, but MiMo (Xiaomi) has the advantage in features.