Claude Opus 4.6 leads SWE-bench at 80.8% vs GPT-5.4's 74.9% — the strongest coding benchmark score of any model. But at $15/1M input vs $2.50, GPT-5.4 is 6× cheaper and has unique desktop-control capabilities. For pure coding quality, Claude Opus 4.6 wins. For cost-efficient work or agentic automation, GPT-5.4 is the better call.
Pick Claude Opus 4.6 when coding quality is non-negotiable and cost is secondary. Pick GPT-5.4 for agentic desktop control or if you need a better price per million tokens.
Claude Opus 4.6 has the highest SWE-bench score of any model (80.8%) with a 1M context window. It is the strongest coding model available for high-stakes engineering work.
Use Claude Opus 4.6 if you want the strongest default. Switch only when cost, speed, or context length matters more than maximum reliability.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
Claude Opus 4.6 is the safest overall answer here when you want the strongest default instead of the lowest list price.
Grok 4 is the lower-cost option to start with when you still need useful output at scale.
GPT-5.4 is the better pick when response speed matters more than maximum reasoning depth.
Claude Opus 4.6 leads all models on SWE-bench with 80.8% — the highest coding benchmark score available.
GPT-5.4 is 6× cheaper at $2.50/1M input vs $15/1M for Opus 4.6.
For most developers, Claude Sonnet 4.6 at 79.6% SWE-bench and $3/1M is the smarter middle ground.
Choose Claude Opus 4.6 for the highest possible coding quality where mistakes have real financial consequences.
Choose GPT-5.4 if you need desktop control, or if cost is a stronger constraint than peak benchmark score.
Most teams should consider Claude Sonnet 4.6 as the practical sweet spot — nearly Opus-level coding at 20% of the price.
This comparison focuses on the models most likely to answer this search intent well, not every model in the directory.
The current #1 coding model by SWE-bench — use when quality is non-negotiable.
Best for agentic automation and desktop control workflows.
Best daily driver for coding and writing — the model most developers actually reach for.
Use these cards as the practical decision layer: what each leading option is good at, and when it becomes the wrong default.
The current #1 coding model by SWE-bench — use when quality is non-negotiable.
Agentic coding, complex multi-step reasoning, and deep research
You run high prompt volumes or cost is a constraint — Sonnet 4.6 delivers 97% of the quality at 20% of the price.
Best for agentic automation and desktop control workflows.
Agentic workflows, desktop automation, and complex multi-step reasoning
You need the highest coding benchmark scores — Claude Opus 4.6 and Sonnet 4.6 lead SWE-bench.
Best daily driver for coding and writing — the model most developers actually reach for.
Daily coding, writing, and long-document work at a strong price-to-quality ratio
You specifically need desktop-control capabilities (GPT-5.4) or the absolute highest coding ceiling (Opus 4.6).
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
Benchmark scores from SWE-bench (coding), ARC-AGI-2 (reasoning), and MMLU (knowledge breadth) — cross-referenced against Chatbot Arena community votes to filter out cherry-picked provider claims.
Input and output costs verified directly against each provider's official API pricing page. Updated whenever a price change is detected. Value-per-dollar is weighted separately from raw benchmark rank.
Advertised context sizes are noted but scored against real-world usability — models that degrade significantly at large contexts are penalised even if the window is technically available.
Production signals matter more than lab scores. We weight Cursor and Windsurf defaults, HackerNews sentiment, developer surveys, and which models teams actually keep using after the honeymoon period.
One-off wins on cherry-picked benchmarks don't move our rankings. We favour models that stay dependable across repeated prompts, diverse task types, and long sessions without degrading.
Time-to-first-token and output throughput from Artificial Analysis speed benchmarks. Latency is categorised from Very fast to Deliberate — relevant when building interactive or high-throughput products.
Data sources
The fastest way to see where the recommendation shifts when your priority changes.
The current #1 coding model by SWE-bench — use when quality is non-negotiable.
Best for agentic automation and desktop control workflows.
Best daily driver for coding and writing — the model most developers actually reach for.
Leads all models on SWE-bench with 80.8% — best coding benchmark score available
1M token context window at standard pricing
Best agentic computer use score at 72.7% on OSWorld
Premium pricing ($15/$75) makes it expensive for high-volume usage
Sonnet 4.6 is only 1.2 points behind on SWE-bench at 5× lower cost
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Useful if you care about ranking shifts, pricing changes, or a better recommendation appearing in this decision path.
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Claude Opus 4.6 leads SWE-bench with 80.8%, making it the strongest coding model available by benchmark. GPT-5.4 scores 74.9%.
Only if coding quality is truly non-negotiable. At $15/1M input vs $2.50 for GPT-5.4, you're paying 6× more for a 5.9 percentage point SWE-bench advantage. Most teams get better ROI from Claude Sonnet 4.6 at $3/1M.
GPT-5.4 has computer-use capabilities — it can control a desktop, click UI elements, and navigate software autonomously via the API. Claude Opus 4.6 doesn't offer this.
For most teams, yes. Claude Sonnet 4.6 scores 79.6% on SWE-bench (only 1.2 points behind Opus) at $3/1M vs $15/1M — 5× cheaper with nearly identical practical coding quality.
Both Claude Opus 4.6 and Claude Sonnet 4.6 have 1M token context windows. GPT-5.4 has 272K — significantly smaller for large codebase or document work.
