Benchmarking the Latest AI Models: The Rise of Extreme Models
The recent benchmarking of 40 new AI models brings to light significant shifts in the Price vs. Performance landscape. With attention focused on Kimi k2.5 and Claude Opus 4.6, the analysis reveals a divide into two extremes: 'God Mode' and 'Flash Mode', rendering mid-range models ineffective.
Key Details
- Kimi k2.5 Situation: Attempts to benchmark Kimi k2.5 were unsuccessful due to persistent 'No Content' errors, likely due to overload. However, Kimi-k2-Thinking performed adequately for complex reasoning tasks at ~15 TPS.
- Speed Dominance: For latency-sensitive applications, Liquid LFM 2.5 emerged as the speediest model clocking in at ~359 tokens/sec, followed by Ministral 3B at ~293 tokens/sec.
- Cost Efficiency: Ministral 3B stands out as the most cost-effective solution, at $0.10/1M input tokens. It is ~17x cheaper and ~40% faster than GPT-5.2 Codex, making it a strong value play against higher-priced options.
The recommendation is to avoid mid-range models that cost between $0.50 - $1.00, as they do not offer competitive performance. Depending on your needs, choose higher-priced models like Opus/GPT-5 for intelligence or opt for cost-effective speed with Liquid/Mistral.
📖 Read the full source: r/LocalLLaMA
👀 See Also
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