llama-3.1-70b-instruct vs zai-glm-4.7

Capability for the money

Not the same tier: zai-glm-4.7 leads llama-3.1-70b-instruct by 66.2 points on coding (LiveCodeBench), for 2.4× the price.

1. Following instructions

   extraction, classification, sticking to a format

   IFBench
   llama-3.1-70b-instruct34.4%

   zai-glm-4.767.9%

   zai-glm-4.7 +33.5

2. Coding

   writing and fixing code

   LiveCodeBench
   llama-3.1-70b-instruct23.2%

   zai-glm-4.789.4%

   zai-glm-4.7 +66.2

3. Tool use

   multi-step agent work against real tools

   τ²-bench
   llama-3.1-70b-instruct15.2%

   zai-glm-4.795.9%

   zai-glm-4.7 +80.7

4. Hard reasoning

   graduate-level science and multi-step analysis

   GPQA Diamond
   llama-3.1-70b-instruct40.9%

   zai-glm-4.785.9%

   zai-glm-4.7 +45.0

Averaged over the benchmarks both models sat, zai-glm-4.7 returns 35.7 points of pass rate per dollar of blended price against 28.4 — 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.