LFM2.5-VL-3B vs Sakana Namazu: Specs & Benchmark Comparison
LFM2.5-VL-3B is developed by Liquid AI, while Sakana Namazu comes from Sakana AI. Both were released in August 2026. LFM2.5-VL-3B has a published size of about 3 billion parameters; Sakana AI has not disclosed the parameter count of Sakana Namazu.
We have 23 benchmark results for LFM2.5-VL-3B and 3 benchmark results for Sakana Namazu, but they were measured on different benchmarks, so there is no like-for-like scoreboard.
Sakana Namazu is available through an API at $0.95 per million input tokens with a 256K-token context window. We do not track a hosted API for LFM2.5-VL-3B, so pricing and context cannot be compared directly.
| Characteristic | LFM2.5-VL-3B | Sakana Namazu |
|---|---|---|
| Company | Liquid AI | Sakana AI |
| Release Date | August 12, 2026 | August 3, 2026 |
| Parameters | 3B | — |
| Multimodal | Yes | Yes |
| Context (input) | — | 256K |
| Context (output) | — | 256K |
| Input Price / 1M | — | $0.95 |
| Output Price / 1M | — | $4.00 |
| Average Score | 63.7% | 92.4% |
Verdict
Both models show equal results — the choice depends on your specific use case.
Both models show comparable average scores: LFM2.5-VL-3B — 0.6, Sakana Namazu — 0.9.
Both models were released around the same time: 8/12/2026 and 8/3/2026.
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Frequently Asked Questions
Which is better for coding — LFM2.5-VL-3B or Sakana Namazu?
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Which has a larger context window — LFM2.5-VL-3B or Sakana Namazu?
The LFM2.5-VL-3B and Sakana Namazu comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the LFM2.5-VL-3B or Sakana Namazu page. See also the complete list of AI model comparisons.