Pick Claude Opus 4.7 for long-running agentic coding workflows or precise instruction following. Pick GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work or classification, extraction, ranking and sub-agent execution at scale. On a tight budget at scale, GPT-5.4 Nano is the value pick.
Claude Opus 4.7 (Anthropic) and GPT-5.4 Nano (OpenAI) are two of the models people most often weigh against each other in 2026. Claude Opus 4.7 is the agentic-coding-focused Opus that traded some long-context recall for long-run reliability. GPT-5.4 Nano is openAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: GPT-5.4 Nano is about 25× cheaper on input ($0.2/$1.25 per 1M tokens vs $5/$25 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Claude Opus 4.7 holds 2.5× more — 1M (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Claude Opus 4.7 is the newer model by about 30 days (released April 16, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Claude Opus 4.7
GPT-5.4 Nano
Provider
Anthropic (US)
OpenAI (US)
Released
April 16, 2026
March 17, 2026
Context window
1M (~1,500 pages)
400K (~600 pages)
Price (in/out)
$5/$25 per 1M tokens
$0.2/$1.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, code
SWE-Bench Verified
87.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-running agentic coding workflows: Claude Opus 4.7 — Its 1M window holds about 2.5× more than GPT-5.4 Nano's 400K in a single prompt.
Precise instruction following: Claude Opus 4.7 — The agentic-coding-focused Opus that traded some long-context recall for long-run reliability — and it carries the larger 1M context.
Task budgets and effort tiers: Claude Opus 4.7 — The agentic-coding-focused Opus that traded some long-context recall for long-run reliability — and it is the newer of the two.
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work: GPT-5.4 Nano — At $0.2/$1.25 per 1M tokens it undercuts Claude Opus 4.7 ($5/$25 per 1M tokens), and that gap compounds at volume.
Classification, extraction, ranking and sub-agent execution at scale: GPT-5.4 Nano — OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning — and it runs cheaper at $0.2/$1.25 per 1M tokens.
A 400K context in the smallest, fastest GPT-5.4 variant: GPT-5.4 Nano — Claude Opus 4.7 is comparatively weak here — long-context recall regressed vs 4.6
Lowest cost at scale: GPT-5.4 Nano — At $0.2/$1.25 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Claude Opus 4.7 — Its 1M window is about 2.5× larger than GPT-5.4 Nano's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-5.4 Nano — At $0.2/$1.25 per 1M tokens it undercuts Claude Opus 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Claude Opus 4.7 — Larger 1M window fits more in one prompt.
Anyone whose priority is long-running agentic coding workflows: Claude Opus 4.7 — It is specifically built for that.
Anyone whose priority is cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work: GPT-5.4 Nano — That is its strongest area.
Claude Opus 4.7: where it fits
The agentic-coding-focused Opus that traded some long-context recall for long-run reliability. Released April 16, 2026 by Anthropic, it is built for long-running agentic coding workflows, precise instruction following, task budgets and effort tiers, and large-codebase operation.
Its trade-offs are real: long-context recall regressed vs 4.6, and superseded by Opus 4.8. At $5 in / $25 out per million tokens, it sits in the premium price band.
GPT-5.4 Nano: where it fits
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Released March 17, 2026 by OpenAI, it is built for cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, classification, extraction, ranking and sub-agent execution at scale, a 400K context in the smallest, fastest GPT-5.4 variant, and text and image input for cheap multimodal pipelines.
Its trade-offs: a nano tier — not built for hard reasoning or frontier coding, no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead), outclassed by GPT-5.4 and GPT-5.4 Mini whenever a task needs real depth, and image input only — no audio or video. At $0.2 in / $1.25 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Claude Opus 4.7 and GPT-5.4 Nano overlap enough that the right pick depends on your specific job. GPT-5.4 Nano costs less per token; Claude Opus 4.7 holds the larger context; and each leads in its own area — Claude Opus 4.7 for long-running agentic coding workflows, GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Claude Opus 4.7 or GPT-5.4 Nano better for coding?
Public SWE-Bench figures are not available for GPT-5.4 Nano, so the honest test is your own repository — run an identical real bug through both. By design, Claude Opus 4.7 leans toward long-running agentic coding workflows while GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Opus 4.7 or GPT-5.4 Nano?
GPT-5.4 Nano is cheaper — $5/$25 per 1M tokens vs $0.2/$1.25 per 1M tokens, roughly 25× apart on input.
Which has the bigger context window?
Claude Opus 4.7 — 1M vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Opus 4.7 and GPT-5.4 Nano together?
Yes — a multi-model platform like LumiChats gives you Claude Opus 4.7, GPT-5.4 Nano and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Claude Opus 4.7 or GPT-5.4 Nano?
Claude Opus 4.7 — released April 16, 2026, about 30 days after GPT-5.4 Nano.
Claude Opus 4.7 vs GPT-5.4 Nano
Anthropic · US | OpenAI · US · Updated June 2026
Quick verdict
Pick Claude Opus 4.7 for long-running agentic coding workflows or precise instruction following. Pick GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work or classification, extraction, ranking and sub-agent execution at scale. On a tight budget at scale, GPT-5.4 Nano is the value pick.
Claude Opus 4.7 (Anthropic) and GPT-5.4 Nano (OpenAI) are two of the models people most often weigh against each other in 2026. Claude Opus 4.7 is the agentic-coding-focused Opus that traded some long-context recall for long-run reliability. GPT-5.4 Nano is openAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GPT-5.4 Nano is about 25× cheaper on input ($0.2/$1.25 per 1M tokens vs $5/$25 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Claude Opus 4.7 holds 2.5× more — 1M (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Claude Opus 4.7 is the newer model by about 30 days (released April 16, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Claude Opus 4.7
GPT-5.4 Nano
Provider
Anthropic (US)
OpenAI (US)
Released
April 16, 2026
March 17, 2026
Context window
1M (~1,500 pages)
400K (~600 pages)
Price (in/out)
$5/$25 per 1M tokens
$0.2/$1.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, code
SWE-Bench Verified
87.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-running agentic coding workflows
Claude Opus 4.7
Its 1M window holds about 2.5× more than GPT-5.4 Nano's 400K in a single prompt.
Precise instruction following
Claude Opus 4.7
The agentic-coding-focused Opus that traded some long-context recall for long-run reliability — and it carries the larger 1M context.
Task budgets and effort tiers
Claude Opus 4.7
The agentic-coding-focused Opus that traded some long-context recall for long-run reliability — and it is the newer of the two.
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work
GPT-5.4 Nano
At $0.2/$1.25 per 1M tokens it undercuts Claude Opus 4.7 ($5/$25 per 1M tokens), and that gap compounds at volume.
Classification, extraction, ranking and sub-agent execution at scale
GPT-5.4 Nano
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning — and it runs cheaper at $0.2/$1.25 per 1M tokens.
A 400K context in the smallest, fastest GPT-5.4 variant
GPT-5.4 Nano
Claude Opus 4.7 is comparatively weak here — long-context recall regressed vs 4.6
Lowest cost at scale
GPT-5.4 Nano
At $0.2/$1.25 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Claude Opus 4.7
Its 1M window is about 2.5× larger than GPT-5.4 Nano's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-5.4 Nano
At $0.2/$1.25 per 1M tokens it undercuts Claude Opus 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Claude Opus 4.7
Larger 1M window fits more in one prompt.
Anyone whose priority is long-running agentic coding workflows
→ Claude Opus 4.7
It is specifically built for that.
Anyone whose priority is cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work
→ GPT-5.4 Nano
That is its strongest area.
Claude Opus 4.7: where it fits
The agentic-coding-focused Opus that traded some long-context recall for long-run reliability. Released April 16, 2026 by Anthropic, it is built for long-running agentic coding workflows, precise instruction following, task budgets and effort tiers, and large-codebase operation.
Its trade-offs are real: long-context recall regressed vs 4.6, and superseded by Opus 4.8. At $5 in / $25 out per million tokens, it sits in the premium price band.
GPT-5.4 Nano: where it fits
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Released March 17, 2026 by OpenAI, it is built for cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, classification, extraction, ranking and sub-agent execution at scale, a 400K context in the smallest, fastest GPT-5.4 variant, and text and image input for cheap multimodal pipelines.
Its trade-offs: a nano tier — not built for hard reasoning or frontier coding, no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead), outclassed by GPT-5.4 and GPT-5.4 Mini whenever a task needs real depth, and image input only — no audio or video. At $0.2 in / $1.25 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Claude Opus 4.7 and GPT-5.4 Nano overlap enough that the right pick depends on your specific job. GPT-5.4 Nano costs less per token; Claude Opus 4.7 holds the larger context; and each leads in its own area — Claude Opus 4.7 for long-running agentic coding workflows, GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Claude Opus 4.7 and GPT-5.4 Nano without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
Is Claude Opus 4.7 or GPT-5.4 Nano better for coding?
Public SWE-Bench figures are not available for GPT-5.4 Nano, so the honest test is your own repository — run an identical real bug through both. By design, Claude Opus 4.7 leans toward long-running agentic coding workflows while GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Opus 4.7 or GPT-5.4 Nano?
GPT-5.4 Nano is cheaper — $5/$25 per 1M tokens vs $0.2/$1.25 per 1M tokens, roughly 25× apart on input.
Which has the bigger context window?
Claude Opus 4.7 — 1M vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Opus 4.7 and GPT-5.4 Nano together?
Yes — a multi-model platform like LumiChats gives you Claude Opus 4.7, GPT-5.4 Nano and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Claude Opus 4.7 or GPT-5.4 Nano?
Claude Opus 4.7 — released April 16, 2026, about 30 days after GPT-5.4 Nano.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.