Compare / Kolibri-1 vs Llama 3.3 70B
Kolibri-1 vs Llama 3.3 70B
Updated November 2026
Verdict
Kolibri-1 scores higher on the Small LM Index: 68.3 vs 40.8. On the 2 benchmarks both labs report, Kolibri-1 wins 2 and Llama 3.3 70B wins 0. Llama 3.3 70B is smaller: it needs about 47.4 GB of memory at 4-bit, against 49.6 GB for Kolibri-1. Only Llama 3.3 70B has a hosted API on OpenRouter ($0.15 per million tokens); the other has to be self-hosted.
Pick Kolibri-1 if…
- you want the strongest model overall
- you work with long documents
- you need a permissive license (Apache-2.0)
Pick Llama 3.3 70B if…
- you have limited memory (about 47.4 GB at 4-bit)
- you want a hosted API rather than running it yourself
- you want the more widely used model (more quantized builds and community support)
Specifications
| Kolibri-1 | Llama 3.3 70B | |
|---|---|---|
| Small LM Index | 68.3 (likely 67–70) | 40.8 (likely 31–51) |
| Lab | Aleph Alpha · Europe | Meta · United States |
| Released | 2026-10-03 | 2024-12-06 |
| Parameters | 78.1B (3.5B active, MoE) | 70.6B (dense) |
| Memory at 4-bit | ~49.6 GB | ~47.4 GB |
| Context window | 1M tokens | 128K tokens |
| Input | text | text |
| Reasoning | Always thinks | No thinking |
| License | Apache-2.0 | Llama 3.3 Community |
| API price / 1M tokens | Self-host only | $0.15 ($0.10 in, $0.32 out) |
| Hugging Face downloads (30 days) | 22.8K | 363.3K |
Benchmarks
Higher is better. Bold marks the winner where both labs report a score. ≈ marks the index model's estimate for a score that wasn't reported, ✓ an independent measurement and * a score measured by another lab.
| Benchmark | Kolibri-1 | Llama 3.3 70B |
|---|---|---|
| MMLU-Pro Knowledge | 80.0 | 68.9 |
| GPQA Diamond Knowledge | 84.3 | 50.5 |
| Humanity's Last Exam Reasoning | 21.5 | ≈ 4 |
| AIME Math | 96.0 | ≈ 54 |
| LiveCodeBench Coding | 85.9 | ≈ 45 |
| SWE-bench Verified Coding | 66.4 | ≈ 21 |
| Terminal-Bench Agentic | 27.7 | — |
| τ²-Bench Agentic | 80.4 | — |
| IFBench Instruction following | 78.1 | — |
| BFCL Agentic | 61.4 | — |
Scores are mostly reported by each lab with its own settings, so small gaps are noise. See the methodology. Open in the interactive comparison to add more models.
Questions
Which is better, Kolibri-1 or Llama 3.3 70B?
Kolibri-1 scores higher on the Small LM Index: 68.3 vs 40.8. On the 2 benchmarks both labs report, Kolibri-1 wins 2 and Llama 3.3 70B wins 0.
Which is cheaper to run?
Only Llama 3.3 70B has a hosted API on OpenRouter ($0.15 per million tokens); the other has to be self-hosted. Llama 3.3 70B is smaller: it needs about 47.4 GB of memory at 4-bit, against 49.6 GB for Kolibri-1.
Which has the longer context window?
Kolibri-1 has the longer context window: 1M tokens against 128K.
Can I use Kolibri-1 and Llama 3.3 70B commercially?
Kolibri-1 is released under Apache-2.0 and Llama 3.3 70B under Llama 3.3 Community. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.
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