Llama 4 (Meta) vs Grok Speech (STT + TTS APIs)
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
Grok Speech (STT + TTS APIs)
xAI's standalone voice APIs -- launched 2026-04-17. Built on the stack that powers Grok Voice, Tesla vehicles, and Starlink customer support. $0.10/hr STT batch, $4.20 per 1M characters TTS, 25+ languages, word-level timestamps + speaker diarization
| Category | Llama 4 (Meta) | Grok Speech (STT + TTS APIs) |
|---|---|---|
| Ease of Use | 5.0 | 7.0 |
| Output Quality | 8.5 | 8.5 |
| Value | 9.0 | 9.0 |
| Features | 9.0 | 8.0 |
| Overall | 7.9 | 8.1 |
Pricing Comparison
| Feature | Llama 4 (Meta) | Grok Speech (STT + TTS APIs) |
|---|---|---|
| Free Tier | Yes | No |
| Starting Price | $0 | $0.10 |
Benchmark Head-to-Head
Llama 4 Maverick (17B/400B MoE) benchmarks — Grok Speech (STT + TTS APIs) 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...
- ✓More features (9 vs 8)
- ✓Has a free tier
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 Grok Speech (STT + TTS APIs) if...
- ✓Easier to use (7 vs 5)
Developers building voice agents, real-time transcription tools, accessibility features, or high-volume TTS workloads where the cost per hour of audio actually matters at scale. Strong fit for phone-call and meeting transcription use cases where xAI's published WER advantage (5.0% on phone-call entities vs. ElevenLabs 12.0%) compounds quickly.
Visit Grok Speech (STT + TTS APIs)Our Verdict
Llama 4 (Meta) and Grok Speech (STT + TTS APIs) are extremely close overall. Your choice comes down to specific needs -- Llama 4 (Meta) is better for developers and teams who need a permissively-licensed open-weights model with strong tooling, long context (scout), or multimodal (maverick), while Grok Speech (STT + TTS APIs) works best for developers building voice agents, real-time transcription tools, accessibility features, or high-volume tts workloads where the cost per hour of audio actually matters at scale.