Capabilities
7-day heat trend
−9.6%Pricing breakdown
Typical 3:1 output-to-input mix, per 1M tokens
Estimated monthly cost by workload
Market position
- Cheaper than 22% of tracked models
- Faster than 32% of tracked models
- Efficiency rank: #89 of 1105
Best suited for
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
About accounts/fireworks/models/minimax-m2p5
MiniMax M2.5 on Fireworks is a lower cached-input-cost long-context chat model for production assistants.
accounts/fireworks/models/minimax-m2p5 is a Text model from Fireworks AI (US). HotON.ai tracks it at $0.30 per 1M input tokens and $1.20 per 1M output tokens, with a 229K-token context window, ~139 tokens/sec throughput and 98.8% availability. Its composite efficiency score is 90/100 at an estimated $0.001 per successful task.
Compare accounts/fireworks/models/minimax-m2p5
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Frequently asked questions
How much does accounts/fireworks/models/minimax-m2p5 cost per 1M tokens?+
accounts/fireworks/models/minimax-m2p5 is tracked at $0.30 per 1M input tokens and $1.20 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.97 per 1M tokens. Figures are illustrative demo data.
What is accounts/fireworks/models/minimax-m2p5 best for?+
General-purpose text generation, chat, summarization and content workloads where broad capability and low cost matter most.
How fast is accounts/fireworks/models/minimax-m2p5?+
accounts/fireworks/models/minimax-m2p5 delivers about 139 tokens/sec with 98.8% tracked availability, suitable for latency-sensitive, real-time applications.
Is accounts/fireworks/models/minimax-m2p5 cheaper than other AI models?+
Within the HotON.ai tracked set, accounts/fireworks/models/minimax-m2p5 is cheaper than 22% of models on input price and ranks #89 of 1105 by overall efficiency.
Related models
Pricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Speed, availability and efficiency are modeled estimates.