When to look beyond Claude Haiku 5.5
A pilot candidate for bounded, high-volume tasks. Recount tokens, inspect the 100K price boundary and migrate request behaviour before changing production routing. Independent same-task Test pending; no HubAI Score. Still, teams should test alternatives when pricing, data controls, output style, integrations or trial limits make a different product more practical.
Keep, add or replace?
Keep Claude Haiku 5.5 if it meets the acceptance checks for your repeated work. Add another tool when it fills one missing capability. Replace it only after a same-work test covers results, total cost and the migration burden.
Before moving the workflow
- For code ai: Check repository access, secrets and tool permissions. Require passing tests and a reviewable diff. Measure accepted changes and developer correction time.
- Run the current and proposed routes on the same approved input. Record accepted results, corrections, reviewer time and total cost; keep vendor claims separate.
- Keep the original files and current workflow available. Check data export, deletion, cancellation and connector revocation before retiring the old service.
Profile check: 8 October 2026. Official Claude Haiku 5.5 source. Record the pilot before renewing or replacing seats.
Choosing for a small business? Start with your core task and budget. Browse all professions for workflow-specific checks.
Code AI · Model AIClaude Sonnet 5.5
A practical large-context baseline for coding and knowledge work with the same published token rates as Sonnet 5. Changed thinking and tool behaviour still require a same-work migration test, so HubAI withholds a score.
- Escalation candidate for unresolved or complex work: confirm the exact overlapping task and measure acceptance and review effort. A larger-model route is not price or feature parity.
- The strongest comparison point is coding, agentic and professional knowledge work that needs a large context window at lower token rates than the opus tier.
- Check metered api and cloud-platform access; availability across claude and paid github copilot plans depends on entitlement, rollout, route and administrator policy before committing paid budget.
Strongest reasonPublished one-million-token context window and 128K maximum outputMain limitationDisabled thinking, forced tools and older computer-use assumptions can require migration work
Profile check: 8 October 2026. Official product source.
Code AI · Model AIGPT-6 Luna
The low-cost baseline in OpenAI's new family, with the same published context and output limits as Sol. It should be tested first for volume workflows, but HubAI assigns no score until reliability, tool use, latency and accepted-output cost are measured independently.
- Shared candidate workload: repeated extraction, classification and transformation. Compare the same labelled inputs, output acceptance rules, tools and complete billed cost; no independent winner is established.
- The strongest comparison point is high-volume extraction, classification, transformation and first-pass agent work that needs low token cost and a large context window.
- Check metered api access; gradual rollout through chatgpt work, codex and eligible github copilot plans, with luna desktop access announced for free and go users before committing paid budget.
Strongest reasonLow published standard rates with a 1,050,000-token context windowMain limitationLower token price is not evidence of adequate task quality or lower complete cost
Profile check: 23 September 2026. Official product source.
BUYER CHECKLISTRun the same test across every alternative.
1. Use one real task2. Record output quality3. Track correction time4. Check privacy terms5. Calculate paid-plan cost