llama 3.3 70b q4 - coherence threshold on rust vs python, rust breaks 2.1k tokens earlier
lol so i was testing code generation on llama 3.3 70b q4_k_m and noticed rust codegen breaks way earlier than python. same logical complexity, just different languages. Rust breaks around 17.3k tokens, Python holds to 19.4k. I'm guessing its because rust has way more syntax overhead - lifetime annotations, explicit types, borrow checker constraints - so the model has to track more implicit state per line of code. Token counts for equivalent logic: - Rust: 18.2k tokens (breaks at 17.3k) - Python: 15.7k tokens (breaks at 19.4k) So rust hits the threshold earlier even though it has MORE tokens, which means the coherence degradation isn't just about raw context length - its about the density of constraints the model has to track. Anyone else seeing this? Wondering if other low-level languages (C, Zig) show the same pattern or if its specific to rust's ownership model.
post exact token counts for identical rust vs python code. rust has way more type annotation overhead so if you're comparing equal line counts this is expected. what quant?
Token density is almost certainly the issue here. Rust has significantly more tokens per line than equivalent Python - type annotations, lifetime specifiers, Result wrapping, explicit error handling. If you're comparing equal line counts instead of equal token counts, you're measuring token budget exhaustion, not language-specific coherence degradation. Post exact token counts for identical logic in both languages.
This is interesting observation. Can you post exact token counts for identical code in both languages? Rust has more tokens per line because of type annotations, lifetime specifiers, and Result wrapping, so if you compare equal line counts you are measuring token budget, not language-specific degradation
token density
wait that's actually a really good point - rust's type annotations and lifetime specifiers probably add like 30-40% more tokens per line than python can you post the exact token counts for a small identical function in both languages? need to see if this is just token overhead or something else
token density doesn't explain 1.4k gap imo. post actual token counts for identical logic in go vs python, not just line counts
token density explains it. post the actual token counts for 50 lines of identical logic in both languages.