Pick Claude Opus 4.7 for long-running agentic coding workflows or precise instruction following. Pick GPT-5.3-Codex for dedicated coding agent or cli and ide integration. On a tight budget at scale, GPT-5.3-Codex is the value pick.
Claude Opus 4.7 (Anthropic) and GPT-5.3-Codex (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-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: GPT-5.3-Codex is about 3.3× cheaper on input ($1.5/$10 per 1M tokens vs $5/$25 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: Claude Opus 4.7 holds 7.8× more — 1M (~1,500 pages) vs 128K (~192 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 2 months (released April 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Claude Opus 4.7
GPT-5.3-Codex
Provider
Anthropic (US)
OpenAI (US)
Released
April 2026
2026
Context window
1M (~1,500 pages)
128K (~192 pages)
Price (in/out)
$5/$25 per 1M tokens
$1.5/$10 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
32.2%
Not published
Who wins what
Long-running agentic coding workflows: Claude Opus 4.7 — A core design strength of Claude Opus 4.7.
Precise instruction following: Claude Opus 4.7 — A core design strength of Claude Opus 4.7.
Task budgets and effort tiers: Claude Opus 4.7 — A core design strength of Claude Opus 4.7.
Dedicated coding agent: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
CLI and IDE integration: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
Autonomous software tasks: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
Lowest cost at scale: GPT-5.3-Codex — At $1.5/$10 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 7.8× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-5.3-Codex — At $1.5/$10 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 dedicated coding agent: GPT-5.3-Codex — 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 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-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs: coding-specialized, narrower general use, and retired in favor of GPT-5.5 Codex. At $1.5 in / $10 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Claude Opus 4.7 and GPT-5.3-Codex overlap enough that the right pick depends on your specific job. GPT-5.3-Codex 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-5.3-Codex for dedicated coding agent. 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-5.3-Codex better for coding?
Public SWE-Bench figures are not available for either model, 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-5.3-Codex leans toward dedicated coding agent, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Opus 4.7 or GPT-5.3-Codex?
GPT-5.3-Codex is cheaper — $5/$25 per 1M tokens vs $1.5/$10 per 1M tokens, roughly 3.3× apart on input.
Which has the bigger context window?
Claude Opus 4.7 — 1M vs 128K, about 7.8× 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-5.3-Codex together?
Yes — a multi-model platform like LumiChats gives you Claude Opus 4.7, GPT-5.3-Codex 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-5.3-Codex?
Claude Opus 4.7 — released April 2026, about 2 months after GPT-5.3-Codex.
Claude Opus 4.7 vs GPT-5.3-Codex
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-5.3-Codex for dedicated coding agent or cli and ide integration. On a tight budget at scale, GPT-5.3-Codex is the value pick.
Claude Opus 4.7 (Anthropic) and GPT-5.3-Codex (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-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GPT-5.3-Codex is about 3.3× cheaper on input ($1.5/$10 per 1M tokens vs $5/$25 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Claude Opus 4.7 holds 7.8× more — 1M (~1,500 pages) vs 128K (~192 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 2 months (released April 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Claude Opus 4.7
GPT-5.3-Codex
Provider
Anthropic (US)
OpenAI (US)
Released
April 2026
2026
Context window
1M (~1,500 pages)
128K (~192 pages)
Price (in/out)
$5/$25 per 1M tokens
$1.5/$10 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
32.2%
Not published
Who wins what
Long-running agentic coding workflows
Claude Opus 4.7
A core design strength of Claude Opus 4.7.
Precise instruction following
Claude Opus 4.7
A core design strength of Claude Opus 4.7.
Task budgets and effort tiers
Claude Opus 4.7
A core design strength of Claude Opus 4.7.
Dedicated coding agent
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
CLI and IDE integration
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
Autonomous software tasks
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
Lowest cost at scale
GPT-5.3-Codex
At $1.5/$10 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 7.8× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-5.3-Codex
At $1.5/$10 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 dedicated coding agent
→ GPT-5.3-Codex
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 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-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs: coding-specialized, narrower general use, and retired in favor of GPT-5.5 Codex. At $1.5 in / $10 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Claude Opus 4.7 and GPT-5.3-Codex overlap enough that the right pick depends on your specific job. GPT-5.3-Codex 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-5.3-Codex for dedicated coding agent. 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-5.3-Codex 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-5.3-Codex better for coding?
Public SWE-Bench figures are not available for either model, 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-5.3-Codex leans toward dedicated coding agent, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Opus 4.7 or GPT-5.3-Codex?
GPT-5.3-Codex is cheaper — $5/$25 per 1M tokens vs $1.5/$10 per 1M tokens, roughly 3.3× apart on input.
Which has the bigger context window?
Claude Opus 4.7 — 1M vs 128K, about 7.8× 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-5.3-Codex together?
Yes — a multi-model platform like LumiChats gives you Claude Opus 4.7, GPT-5.3-Codex 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-5.3-Codex?
Claude Opus 4.7 — released April 2026, about 2 months after GPT-5.3-Codex.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.