Posts tagged reasoning
14 posts about reasoning.
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GPT-6 Luna vs GPT-5.6 Luna: Half the Price, Half the Words
GPT-6 Luna wrote 0.55x the words of GPT-5.6 Luna on goal-only prompts, matched it with the parts named (74 vs 69 of 80), and cost $0.81 vs $1.61 per 1,000.
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GPT-6.1 Sol vs Claude Sonnet 5.5: Same $2/$10, Half the Cost per Task
GPT-6.1 Sol and Sonnet 5.5 both list at $2/$10. Sol cost 0.49x per task in our tests and $0.72 vs $2.74 at a matched index score; Sonnet scores higher at max.
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Claude Sonnet 5.5 vs Sonnet 5: Same Price, 80% Less per Task
Sonnet 5.5 cost $0.0041 per task vs Sonnet 5's $0.021 at the same $2/$10. Below xhigh effort it wrote its working into 68 of 156 answer-only replies.
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Claude Opus 5.5 vs Opus 5: Same Answers, Half the Output Tokens
Opus 5.5 lists 20% under Opus 5, so only savings past 20% count. At equal prices it ran 56% cheaper on single-shot tasks and 22% cheaper in a tool loop.
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GPT-6 Astra Reasoning Effort: max Costs 2.3x low for the Same Answers
Measured on 11 verified tasks: none fails 17 of 33, disabled does not disable, max costs 2.3x low, and Astra is 1.6x GPT-5.6 Sol per correct answer.
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LLM Structured Outputs: 4 of 12 APIs Return Valid but Wrong JSON
Structured outputs measured on 12 LLM APIs: 100% schema-valid JSON, wrong values on 4 models with thinking on, same call billed 30 to 4,959 prompt tokens.
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LLM Thinking Controls: What 13 Models Accept, Ignore, or Enforce
reasoning_effort and thinking_budget across 13 LLM APIs: three vendors enforce budgets to the token, others silently ignore them, a cap of 16 can burn 97.
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Claude Opus 5 vs Opus 4.8, Measured: Same Price, 3x Apart
Opus 5 and Opus 4.8 share a $5/$25 rate card, yet Opus 5 billed 3.1x more on identical tasks out of the box. Where it goes, and the switch that closes it.
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Gemini 3.6 Flash: the Thinking Dial That Moves Cost 30x (Measured)
Gemini 3.6 Flash bills reasoning you never see, and one request setting swings the same task's cost up to 30x. Measured across five task types, with the catch.
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GPT-5.6 Prompting Guide: Two Defaults That Bill 1.5x and 10x More
GPT-5.6 defaults are expensive: omitting reasoning_effort bills 1.5x vs 'none'; unmarked prefixes cost 10x cached reads. Request-shape playbook, measured.
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Kimi K3 API Pricing, Measured: Turn Off the 'Always-On' Reasoning
Kimi K3's docs say reasoning can't be disabled. reasoning_effort:'none' works and cuts simple queries 6x. Measured: effort dial, cache floor, 9-language rates.
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LLM Token Usage: Why a 4-Token Answer Bills 217 Tokens
Measured across GPT-5.6, Claude Fable 5, Qwen3.7-max and five more families: reasoning dominates the output bill. How to read every usage field, and cap them.
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GPT-5.6 Cost Guide: Prompt Caching 90% Off, Reasoning Effort
GPT-5.6's two cost levers, measured: explicit breakpoints bill cached input at 10% of the rate, and not sending reasoning_effort bills 1.5x as much as none.
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GLM 5.2 Reasoning Effort: the Setting That Cuts Cost 20x (Measured)
Same coding answer: $0.0031 with reasoning effort set right vs $0.062 on GLM 5.2's unbounded default. 20x cheaper, 30x faster. How to set the dial per task.