Llm model selection

LLM Model Selection Skill

Choosing the right model for the task — power vs. cost vs. speed.

⚠️ Staleness Warning

This skill depends on rapidly evolving technology. Model capabilities, pricing, and availability change frequently.

Refresh triggers:

• New model announcements (Claude, GPT, Gemini, etc.)
• Significant pricing changes
• Context window expansions
• New capability tiers

Last validated: March 2026 (Claude 4.6 generation)

Check current state: Anthropic Models, OpenAI Models

---

The Core Question

Is Claude Opus 4.6 overkill?

Sometimes yes, sometimes no. Match the model to the task.

Claude 4 Model Family (Current)

Model	API ID	Best For	Input/Output (MTok)	Context	Max Output
Opus 4.6	claude-opus-4-6	Building agents, most intelligent	$5 / $25	200K (1M beta)	128K
Sonnet 4.6	claude-sonnet-4-6	Best speed + intelligence balance	$3 / $15	200K (1M beta)	64K
Haiku 4.5	claude-haiku-4-5-20251001	Near-frontier intelligence, fastest	$1 / $5	200K	64K

All Claude 4 models support:

• Extended thinking
• Vision (images)
• Tool use
• Priority Tier access

Opus 4.6 and Sonnet 4.6 additionally support:

• Adaptive thinking (dynamic reasoning depth)
• 1M token context window (beta, via context-1m-2025-08-07 header — long context pricing applies beyond 200K)

AWS Bedrock IDs: anthropic.claude-opus-4-6-v1, anthropic.claude-sonnet-4-6 GCP Vertex AI IDs: claude-opus-4-6, claude-sonnet-4-6

Model Tiers

Tier	Models	Best For	Relative Cost
Frontier	Claude Opus 4.6, GPT-5.2/5.3/Codex, o3, o1-pro	Complex reasoning, architecture, novel problems	$$$$$
Capable	Claude Sonnet 4.6, GPT-5.1/Codex, GPT-4.1, GPT-4o, Gemini 2.5/3 Pro, o4-mini	Most coding tasks, refactoring, debugging	$$$
Efficient	Claude Haiku 4.5, GPT-5 mini, GPT-4.1 mini/nano, GPT-4o mini, Gemini 2.5 Flash, Gemini 3 Flash	Simple edits, formatting, boilerplate	$

When Opus 4.6 IS Worth It

• ✅ Architecture decisions — Multi-file refactoring, system design
• ✅ Novel problem-solving — No clear pattern to follow
• ✅ Complex reasoning chains — Many dependencies, edge cases
• ✅ Long context understanding — Large codebases, documentation
• ✅ Nuanced judgment — Taste, style, UX decisions
• ✅ Learning sessions — Bootstrap learning, skill development
• ✅ Meditation/self-actualization — Meta-cognitive operations
• ✅ Extended thinking tasks — Deep analysis requiring internal reasoning

When Opus 4.6 IS Overkill

• ❌ Simple file edits — Renaming, adding imports
• ❌ Boilerplate generation — CRUD, scaffolding
• ❌ Format conversion — JSON ↔ YAML, etc.
• ❌ Syntax fixes — Lint errors, typos
• ❌ Documentation updates — README badges, version bumps

How LLM Choice Affects the AI assistant

Capability	Frontier (Opus 4.6)	Capable (Sonnet 4.6)	Fast (Haiku 4.5)
Complex refactoring	Excellent	Excellent	Good
Context retention	200K / 1M (beta)	200K / 1M (beta)	200K tokens
Extended thinking	Full depth	Supported	Supported
Adaptive thinking	Yes	Yes	No
Max output tokens	128K	64K	64K
Nuanced judgment	Excellent	Good	Basic
Speed	Moderate	Fast	Fastest
Cost per session	$2-5	$0.50-2	$0.05-0.30
Multi-step planning	Excellent	Excellent	Good
Error recovery	Self-corrects	Self-corrects	Needs guidance

the AI's Cognitive Power by Model

Opus 4.6:     [████████████████████] Full cognitive architecture + deep thinking
Sonnet 4.6:   [██████████████████░░] Most capabilities, excellent for coding
Haiku 4.5:    [██████████████░░░░░░] Solid baseline, fast responses

With Opus 4.6, the AI assistant can:

• Maintain 7±2 working memory rules across long sessions
• Execute complex meditation protocols with extended thinking
• Perform genuine meta-cognitive reflection
• Handle multi-file architecture changes
• Learn new skills through bootstrap learning

With Sonnet 4.6, the AI assistant gets:

• Excellent coding capabilities (recommended for most development)
• 1M context window (beta) for large codebases
• 64K max output tokens + adaptive thinking
• Good cost-to-capability ratio
• Extended thinking support

With Haiku 4.5, the AI assistant has:

• Near-frontier intelligence at lowest cost
• Fastest response times
• Good for routine operations

Cost Optimization Strategy

Session Type	Recommended Model	Rationale
Architecture/design	Opus 4.6	Worth the cost for complex decisions
Feature development	Sonnet 4.6	Best balance of capability and cost
Bug fixes	Sonnet 4.6 or Haiku 4.5	Depends on complexity
Documentation	Haiku 4.5	Simple edits, fast turnaround
Large codebase analysis	Sonnet 4.6 (1M beta)	Extended context window up to 1M tokens

Knowledge Cutoffs

Model	Reliable Knowledge	Training Data
Opus 4.6	May 2025	Aug 2025
Sonnet 4.6	Aug 2025	Jan 2026
Haiku 4.5	Feb 2025	Jul 2025

Auto Model Selection ⚠️

When using Auto in VS Code Copilot, the model switches dynamically based on task complexity. the AI assistant cannot detect which model is currently running.

Tasks That REQUIRE Opus 4.5 (Warn User)

Task	Why Opus Required
Meditation/consolidation	Meta-cognitive protocols need full reasoning depth
Self-actualization	Comprehensive architecture assessment
Complex architecture refactoring	Multi-file changes, deep context
Bootstrap learning (new skills)	Skill acquisition needs maximum capability
Connection validation/dream	Architecture maintenance requires full architecture context
Adaptive thinking tasks	Opus 4.6 uses dynamic reasoning depth for optimal results

Warning Protocol

When user requests an Opus-level task while potentially on Auto/lesser model:

⚠️ Model Check: This task works best with Claude Opus 4.6. If you're using Auto model selection, please manually select Opus from the model picker for optimal results. Continue anyway?

Safe for Any Model

• Simple file edits, formatting
• Documentation updates
• Quick Q&A
• Code review (Sonnet+ recommended)
• Bug fixes (depends on complexity)

Practical Guidance

When to Upgrade Model Mid-Session

If you notice:

• Repeated mistakes on the same issue
• Losing context from earlier in conversation
• Superficial answers to complex questions
• Failure to see cross-file dependencies

→ Consider switching to a more capable model

When to Downgrade

If you're doing:

• Repetitive mechanical edits
• Simple Q&A
• Format conversions
• Quick lookups

→ Save cost with a faster model

The the AI assistant Recommendation

For architecture evolution and complex cognitive tasks: → Always use Opus 4.6 — The cognitive architecture demands full capability

For production deployment, user-facing work: → Default to Sonnet 4.6 — Best balance of capability and cost → Allow Opus for complex tasks — User can request escalation

Token Economics

Operation	Approximate Tokens	Opus 4.6 Cost	Sonnet 4.6 Cost
Read large file	2,000-5,000	$0.03-0.08	$0.006-0.015
Complex refactor	10,000-20,000	$0.15-0.30	$0.03-0.06
Full session	50,000-150,000	$0.75-2.25	$0.15-0.45
Meditation	30,000-80,000	$0.45-1.20	$0.09-0.24