Compare / Kolibri-1 vs DeepSeek-R1-Distill-Llama-70B
Kolibri-1 vs DeepSeek-R1-Distill-Llama-70B
Updated November 2026
Verdict
Kolibri-1 scores higher on the Small LM Index: 68.3 vs 50.1. On the 3 benchmarks both labs report, Kolibri-1 wins 3 and DeepSeek-R1-Distill-Llama-70B wins 0. DeepSeek-R1-Distill-Llama-70B is smaller: it needs about 47.4 GB of memory at 4-bit, against 49.6 GB for Kolibri-1. Neither model has a hosted API on OpenRouter, so you would run both yourself.
Pick Kolibri-1 if…
- you want the strongest model overall
- you mostly write code
- you need math and reasoning
- you work with long documents
Pick DeepSeek-R1-Distill-Llama-70B if…
- you have limited memory (about 47.4 GB at 4-bit)
Specifications
| Kolibri-1 | DeepSeek-R1-Distill-Llama-70B | |
|---|---|---|
| Small LM Index | 68.3 (likely 67–70) | 50.1 (likely 45–55) |
| Lab | Aleph Alpha · Europe | DeepSeek · China |
| Released | 2026-10-03 | 2025-01-20 |
| 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 | Always thinks |
| License | Apache-2.0 | MIT |
| API price / 1M tokens | Self-host only | Self-host only |
| Hugging Face downloads (30 days) | 22.8K | 30.5K |
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 | DeepSeek-R1-Distill-Llama-70B |
|---|---|---|
| MMLU-Pro Knowledge | 80.0 | ≈ 72 |
| GPQA Diamond Knowledge | 84.3 | 65.2 |
| Humanity's Last Exam Reasoning | 21.5 | ≈ 6 |
| AIME Math | 96.0 | 70.0 |
| LiveCodeBench Coding | 85.9 | 57.5 |
| SWE-bench Verified Coding | 66.4 | ≈ 31 |
| 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 DeepSeek-R1-Distill-Llama-70B?
Kolibri-1 scores higher on the Small LM Index: 68.3 vs 50.1. On the 3 benchmarks both labs report, Kolibri-1 wins 3 and DeepSeek-R1-Distill-Llama-70B wins 0.
Which is cheaper to run?
Neither model has a hosted API on OpenRouter, so you would run both yourself. DeepSeek-R1-Distill-Llama-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 DeepSeek-R1-Distill-Llama-70B commercially?
Kolibri-1 is released under Apache-2.0 and DeepSeek-R1-Distill-Llama-70B under MIT. 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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