strands-decider-26B-A4B-gemma4-v1-2610 vs strands-decider-2B-qwen3.5-v1-2610
strands-decider-26B-A4B-gemma4-v1-2610 and strands-decider-2B-qwen3.5-v1-2610 have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | strands-decider-26B-A4B-gemma4-v1-2610 | strands-decider-2B-qwen3.5-v1-2610 |
|---|---|---|
| Provider | amazon | amazon |
| Decision Index score | — | — |
| Calibration error (ECE) | — | — |
| Median latency (p50) | — | — |
| Cost per 1,000 decisions | — | — |
| Parameters | 26B | 2B |
| Open weights | Yes | Yes |
| Question types | — | — |
| Mechanism | — | — |
| License | — | — |
FAQ
Is strands-decider-26B-A4B-gemma4-v1-2610 or strands-decider-2B-qwen3.5-v1-2610 more accurate?
At least one of the two has no Jev Decision Index score yet, so their accuracy cannot be compared here.
Which is better calibrated, strands-decider-26B-A4B-gemma4-v1-2610 or strands-decider-2B-qwen3.5-v1-2610?
No calibration difference between strands-decider-26B-A4B-gemma4-v1-2610 and strands-decider-2B-qwen3.5-v1-2610 is recorded yet.
Is strands-decider-26B-A4B-gemma4-v1-2610 or strands-decider-2B-qwen3.5-v1-2610 cheaper per 1,000 decisions?
A hosted price is not recorded for both models; open-weight models cost the compute you run them on.
Cost per 1,000 decisions assumes 200 input tokens per decision. Pricing is indicative — confirm with the provider before production use. Highlighted values indicate the better figure for that row.