jamba-large-1.7 vs jamba-mini-1.7

Capability for the money

jamba-large-1.7 is 14.0× dearer for 12.0 points on coding (LiveCodeBench) — worth it only if that is your bottleneck.

1. Following instructions

   extraction, classification, sticking to a format

   IFBench
   jamba-large-1.735.2%

   jamba-mini-1.731.4%

   jamba-large-1.7 +3.8

2. Coding

   writing and fixing code

   LiveCodeBench
   jamba-large-1.718.1%

   jamba-mini-1.76.1%

   jamba-large-1.7 +12.0

3. Tool use

   multi-step agent work against real tools

   τ²-bench
   jamba-large-1.713.5%

   jamba-mini-1.712.6%

   jamba-large-1.7 +0.9

4. Hard reasoning

   graduate-level science and multi-step analysis

   GPQA Diamond
   jamba-large-1.739.0%

   jamba-mini-1.732.2%

   jamba-large-1.7 +6.8

Averaged over the benchmarks both models sat, jamba-mini-1.7 returns 82.3 points of pass rate per dollar of blended price against 7.6 — 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.