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Daily blended price ($/1M) — recorded each day, builds into a trend over time.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-05-11 · Source: alfredpros_reference_catalog
Code generation, refactoring and review, and developer-tooling workloads with large context.
A finetuned 7 billion parameters Code LLaMA - Instruct model to generate Solidity smart contract using 4-bit QLoRA finetuning provided by PEFT library.
codellama-7b-instruct-solidity is a Code model from Alfredpros (US). HotON.ai tracks it at $0.80 per 1M input tokens and $1.20 per 1M output tokens, with a 4K-token context window. Its composite efficiency score is 88/100 at an estimated $0.002 per successful task.
codellama-7b-instruct-solidity is tracked at $0.80 per 1M input tokens and $1.20 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $1.10 per 1M tokens. Figures are illustrative demo data.
Code generation, refactoring and review, and developer-tooling workloads with large context.
codellama-7b-instruct-solidity supports up to a 4K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, codellama-7b-instruct-solidity is cheaper than 35% of models on input price and ranks #315 of 535 by overall efficiency.
Yes — qwen3-coder-flash is a lower-cost option at $0.98 per 1M output tokens, while still covering similar Code use cases. Compare them side by side on HotON.ai.
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HotON.ai — codellama-7b-instruct-solidity (Alfredpros): $0.80/1M input, $1.20/1M output, as of 2026-05-11. https://hoton.ai/en/models/alfredpros-codellama-7b-instruct-solidityPricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.