jamba-mini-1.7 vs llama-3.1-8b-instruct

Capability for the money

jamba-mini-1.7 is 1.3× dearer for 6.3 points on hard reasoning (GPQA Diamond) — worth it only if that is your bottleneck.

1. Following instructions

   extraction, classification, sticking to a format

   IFBench
   jamba-mini-1.731.4%

   llama-3.1-8b-instruct28.6%

   jamba-mini-1.7 +2.8

2. Coding

   writing and fixing code

   LiveCodeBench
   jamba-mini-1.76.1%

   llama-3.1-8b-instruct11.6%

   llama-3.1-8b-instruct +5.5

3. Tool use

   multi-step agent work against real tools

   τ²-bench
   jamba-mini-1.712.6%

   llama-3.1-8b-instruct16.4%

   llama-3.1-8b-instruct +3.8

4. Hard reasoning

   graduate-level science and multi-step analysis

   GPQA Diamond
   jamba-mini-1.732.2%

   llama-3.1-8b-instruct25.9%

   jamba-mini-1.7 +6.3

Averaged over the benchmarks both models sat, llama-3.1-8b-instruct returns 103.1 points of pass rate per dollar of blended price against 82.3 — 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. And a benchmark is not your workload — it narrows the shortlist, it does not pick for you.