gpt-5.6-terra vs llama-3.3-70b-versatile

Capability for the money

Not the same tier: gpt-5.6-terra leads llama-3.3-70b-versatile by 42.7 points on hard reasoning (GPQA Diamond), for 7.0× the price.

1. Following instructions

   extraction, classification, sticking to a format

   IFBench
   gpt-5.6-terra71.2%

   llama-3.3-70b-versatile47.1%

   gpt-5.6-terra +24.1

2. Tool use

   multi-step agent work against real tools

   τ²-bench
   gpt-5.6-terra86.3%

   llama-3.3-70b-versatile26.6%

   gpt-5.6-terra +59.7

3. Hard reasoning

   graduate-level science and multi-step analysis

   GPQA Diamond
   gpt-5.6-terra92.5%

   llama-3.3-70b-versatile49.8%

   gpt-5.6-terra +42.7

Averaged over the benchmarks both models sat, llama-3.3-70b-versatile returns 64.3 points of pass rate per dollar of blended price against 18.5 — 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 coding score for one of these models, so that lens is omitted. And a benchmark is not your workload — it narrows the shortlist, it does not pick for you.