jamba-large-1.6 vs llama-3.1-8b-instruct

Capability for the money

jamba-large-1.6 is 17.5× dearer for 12.8 points on hard reasoning (GPQA Diamond) — worth it only if that is your bottleneck.

1. Coding

   writing and fixing code

   LiveCodeBench
   jamba-large-1.617.2%

   llama-3.1-8b-instruct11.6%

   jamba-large-1.6 +5.6

2. Hard reasoning

   graduate-level science and multi-step analysis

   GPQA Diamond
   jamba-large-1.638.7%

   llama-3.1-8b-instruct25.9%

   jamba-large-1.6 +12.8

Averaged over the benchmarks both models sat, llama-3.1-8b-instruct returns 93.8 points of pass rate per dollar of blended price against 8.0 — the ratio that decides whether the dearer model earns its rate.

Each figure is a pass rate: the share of that test set the model answered correctly, measured by a third party rather than self-reported by the lab. Rows are different tests of different difficulty, so compare a model against the other model, not one row against the next. No published following instructions or tool use score for one of these models, so those lenses are omitted. And a benchmark is not your workload — it narrows the shortlist, it does not pick for you.