topic · 14 notes
LLM Pricing & Cost, as it ships.
Price per million tokens is only the start of what a model costs; tokens per task, retries, caching and the choice of model per step decide the bill. These notes track pricing changes and work through the cost of real workloads.
What the OpenAI Decisions API beta exposes, and when a local decision model wins
OpenAI Decisions API beta returns typed answers 10x faster than Responses on gpt-6-luna, but OpenAI lists no price or latency. Decider 2B: 115 ms median.
GLM 5.3 Flash after a month on Wagtail: 1B of 2B tokens, $68, 4 kWh
GLM 5.3 Flash took 1B of Wagtail's 2B September tokens for $68 and 4 kWh. A wrong-model run, provider limits and R&D, not the model, took the rest.
Fireworks' Ember-1: Kimi K3 with 35-50% shorter reasoning, no weights or price
Ember-1, Fireworks' post-trained Kimi K3, reports K3-level scores with about 40% fewer tokens. Two-week serverless preview, no weights, licence or price.
What the Mercury 2.5 770 tokens per second benchmark buys in an agent loop
Artificial Analysis measured Mercury 2.5 at 770.4 output tokens/sec, 2nd of 174 for speed, 90th for intelligence, no TTFT published, 35M output tokens.
What GPT-6 Sol and Luna pricing and context window claims rest on
GPT-6 Sol at $2/$10 and Luna at $0.10/$0.50 per 1M tokens, plus a 1M context window, come from Hacker News commenters, not OpenAI's 22 September 2026 page.
Claude Opus 5.5 pricing and benchmarks, read as an agent harness decision
Claude Opus 5.5 shipped 22 September 2026 at $4/$20 per million tokens with $0.20 cache reads, 66.4% on Terminal-Bench 4.0 and a claimed 40% cost drop.
HarnessTax: the same coding model, similar success, up to 5x the cost across harnesses
HarnessTax ran 7 models in Claude Code, Codex CLI and Pi: success moved about 2%, cost up to 5x. Claude Code cost about 2x Pi on SWE-bench Lite.
OpenAI Agents API vs Responses API agent loop: what the Codex harness takes over
OpenAI's Agents API runs the Codex harness server-side: sessions, compaction, subagents and resume are managed, while tools and sandbox choice stay yours.
RTK token savings AI coding cost benchmark: 89% fewer tokens, no lower bill
Quesma spent $1,500+ on Terminal-Bench 2.1 runs with and without RTK: Claude Code with Fable 5.0 was 5% cheaper, OpenCode with DeepSeek V4 Pro 5% pricier.
DeepSeek v4.1 Flash pricing, benchmarks, and 890 bytes per token
DeepSeek V4.1-Flash is a 552B MoE with 8B active params at prefill, 16B at decode, 890 bytes per token KV cache, and off-peak rates at 50% of peak.
GPT-6 Astra code review cost evaluation: 4% more bugs at 2.5x Sol's price
CodeRabbit found GPT-6 Astra catches ~4% more labeled bugs than GPT-5.6 Sol overall and 20% more cross-file, at $10/$50 per 1M tokens versus Sol's $4/$20.
GPT-5.6 Sol drops 20% per token, and the agent stacks that won't feel it
OpenAI cut GPT-5.6 Sol pricing 20%. The class-level breakdown isn't confirmed, and both agent stacks in the sources bill via Codex seats, not tokens.
DeepMind open sources WeatherNext Cyclones, a 1,000-member ensemble at 28km
WeatherNext Cyclones runs 1,000-member ensembles at 28x28km and produces a 15-day forecast in under a minute on a TPU. It is now open source.
Databricks cut AI coding spend 70% by chasing the efficiency frontier
Databricks reports a 70% cut in AI coding spend via internal evals, a meta-harness called Omnigent, and an AI Gateway. Figures are self-reported.
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