Llama 4 (Meta) vs gpt-oss (OpenAI)
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
gpt-oss (OpenAI)
OpenAI's FIRST open-weight models -- gpt-oss-120b (single 80GB GPU, near parity with o4-mini on reasoning) and gpt-oss-20b (runs on 16GB edge devices). Apache 2.0. Launched 2025-08-05. gpt-oss-safeguard ships in 2026 as the safety-tuned variant
| Category | Llama 4 (Meta) | gpt-oss (OpenAI) |
|---|---|---|
| Ease of Use | 5.0 | 7.0 |
| Output Quality | 8.5 | 8.5 |
| Value | 9.0 | 10.0 |
| Features | 9.0 | 7.0 |
| Overall | 7.9 | 8.1 |
Pricing Comparison
| Feature | Llama 4 (Meta) | gpt-oss (OpenAI) |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Benchmark Head-to-Head
Llama 4 Maverick (17B/400B MoE) benchmarks — gpt-oss (OpenAI) 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 7)
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 gpt-oss (OpenAI) if...
- ✓Easier to use (7 vs 5)
- ✓Better value for money (10/10)
Developers who want OpenAI-brand open-weight reasoning models for self-hosting or fine-tuning. Particularly good for single-GPU deployments (gpt-oss-120b on one 80GB card) or edge-device reasoning (gpt-oss-20b on 16GB consumer GPUs / Apple Silicon). Also good as a reliable baseline when comparing newer open-weight releases.
Visit gpt-oss (OpenAI)Our Verdict
Llama 4 (Meta) and gpt-oss (OpenAI) 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 gpt-oss (OpenAI) works best for developers who want openai-brand open-weight reasoning models for self-hosting or fine-tuning.