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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 2026-04-28 · Source: legacy_model_catalog
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
A 7.3B parameter model that outperforms Llama 2 13B on all benchmarks, with optimizations for speed and context length.
mistral-7b-instruct-v0.1 is a Text model from Mistral AI (US). HotON.ai tracks it at $0.11 per 1M input tokens and $0.19 per 1M output tokens, with a 3K-token context window. Its composite efficiency score is 88/100 at an estimated $0.000 per successful task.
mistral-7b-instruct-v0.1 is tracked at $0.11 per 1M input tokens and $0.19 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.17 per 1M tokens. Figures are illustrative demo data.
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
mistral-7b-instruct-v0.1 supports up to a 3K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, mistral-7b-instruct-v0.1 is cheaper than 78% of models on input price and ranks #349 of 535 by overall efficiency.
Yes — nemotron-3-nano-30b-a3b is a lower-cost option at $0.20 per 1M output tokens, while still covering similar Text use cases. Compare them side by side on HotON.ai.
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HotON.ai — mistral-7b-instruct-v0.1 (Mistral AI): $0.11/1M input, $0.19/1M output, as of 2026-04-28. https://hoton.ai/en/models/mistralai-mistral-7b-instruct-v0-1Pricing 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.