What happens behind the scenes when we change effort for same LLM models?
This is a very good question and the answers are different for different models.---Deepseek v4 Pro has three modes: no thinking, thinking ("high"), very good thinking ("max"). You MUST be very thorough in your thinking and comprehensively decompose the problem to resolve the root cause, rigorously stress-testing your logic against all potential paths, edge cases, and adversarial scenarios. Specified the desired effort level in the system message. > 2.
- ▪This is a very good question and the answers are different for different models.---Deepseek v4 Pro has three modes: no thinking, thinking ("high"), very good thinking ("max").
- ▪You MUST be very thorough in your thinking and comprehensively decompose the problem to resolve the root cause, rigorously stress-testing your logic against all potential paths, edge cases, and adversarial scenarios.
- ▪Specified the desired effort level in the system message. > 2.
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Story provenance
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Record
| Original publisher | Ycombinator |
| Canonical URL | https://news.ycombinator.com/item?id=49048125 |
| Publication time | Sat, 25 Jul 2026 14:59:52 +0000 |
| Retrieval time | 2026-07-25T15:12:16.632Z |
| Last seen | 2026-07-25T15:12:16.632Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | kOyI8_clyt_w |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
This is a very good question and the answers are different for different models.---Deepseek v4 Pro has three modes: no thinking, thinking ("high"), very good thinking ("max"). Max is implemented as follows:https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro/blob/main...> When reasoning_effort="max" is set, a special prefix is prepended at the very beginning of the prompt (before the system message) to instruct the model to maximize its reasoning depth: > > Reasoning Effort: Absolute maximum with no shortcuts permitted. You MUST be very thorough in your thinking and comprehensively decompose the problem to resolve the root cause, rigorously stress-testing your logic against all potential paths, edge cases, and adversarial scenarios.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Ycombinator.