
Opus 4.8 vs Claude Opus 5
The reasoning king — deepest thinking, premium price. vs The new Anthropic flagship — benched on all 45 one-shot builds the day it landed.
Head-to-head verdict: Opus 4.8 wins 9–4.
What I tested — same prompt, two models
I run the same fixed prompt set through every new model the day it drops — same string, one shot, single HTML file out — and I score the result 0–10 on whether it ran, how close it hit the brief, and how good it looked. Below is what came out when I gave the exact same prompts to Opus 4.8 and Claude Opus 5, side by side, on 22 shared tasks inside the Agent Operating System.
Both models were given identical prompts inside the Agent Operating System — no help, no iteration, no "best of N" tricks. I run each prompt once, save the HTML file the model produces, and score it 0–10 on whether it ran, how close it hit the brief, and how good it looked. The scoring is mine. The verdicts below are pulled from my source comparison guides at agentos.guide where I publish every score and the reasoning behind it.
Opus 4.8 · The default when the build has to ship on the first prompt — Opus is the safety net inside Agent OS for hard one-shots.
Claude Opus 5 · Benched on all 45 GoldieBench tasks via API on release day, incremental deploys as scores landed.
Side-by-side on 47 shared tasks
Click any cell to play that model's actual one-shot attempt. Medals are derived from my 0–10 scores per task (highest = 🥇, second = 🥈, third = 🥉).
Where Opus 4.8 beat Claude Opus 5
The tasks where I gave Opus 4.8 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
What I saw: 27KB · plays clean · three, webgl
What I saw: 20KB · plays clean · three, webgl (re-rolled)
What I saw: 9KB · plays clean · input
What I saw: 17KB · plays clean · audio
What I saw: 13KB · animation runs but no input response · webgl
Where Claude Opus 5 beat Opus 4.8
The tasks where I gave Claude Opus 5 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
What I saw: Gorgeous atmospheric frozen world — aurora, moon glow, snowy terrain, low-poly pines, ruins, and a well-modeled armored third-person character with sword DRAWN and full HUD (compass, health/stam, kill counter). Strong and clearly shippable, but no visible enemies/dragon or combat…
What I saw: Gorgeous detailed player jet, full flight HUD, functional radar showing 4 bogeys, terrain warning, and afterburner/boost systems all read as a shippable 3D dogfighter. Slightly held back because the screenshot shows no visible enemy aircraft in view or active combat/tracers, leav…
What I saw: Gorgeous stylized dragon with articulated wings, spine and belly plates plus a polished full HUD (hull/fury/alt/spd/combo, rings, kills, hostiles, distance marker) — clearly shippable and combat-ready with 5 hostiles tracked. Held back from the top by no visible neon rings or ene…
What I saw: Gorgeous cohesive art direction — detailed low-poly car with wheels/shadow, layered cityscape, refined HUD with integrity/velocity/wanted stars and a live minimap showing cop (red) and player markers plus traffic (purple car visible). Pursuit=2 and full control set (fire/steal/bo…
Strengths & weaknesses I logged
Opus 4.8
Strengths
- Most consistent across the Goldie Bench bench — no weak build, 8.46/10 average
- Deepest one-shot reasoning, especially on game-feel and physics
- Extended thinking mode handles up to 1M tokens of context
Trade-offs
- 5–10× the per-token cost of every other model on the bench
- Less flair on cinematic visuals than GLM-5.2 — playing it safer wins on accuracy, costs you on showpiece moments
Claude Opus 5
Strengths
- Frontier-class coding + agentic reasoning (Claude 5 family)
- 1M-token context — reads an entire codebase in one call
- Benched here with skill-infused game prompts the day of release
Trade-offs
- Premium pricing ($5/$25 per M) — route the everyday 90% to cheaper lanes
- Reasoning-by-default eats token budgets unless tuned per call
Pricing & context — the spec sheet
| Spec | Opus 4.8 | Claude Opus 5 |
|---|---|---|
| Vendor | Anthropic | Anthropic |
| Context window | 200,000 tokens (1M with extended thinking) | 1,000,000 tokens |
| Price | $15 / $75 per M tokens | $5 / $25 per M |
| Pricing detail | Premium pricing via the Anthropic API: $15 per million input tokens, $75 per million output tokens. Extended thinking is included but adds latency. | Anthropic's brand-new flagship — the first Opus of the Claude 5 family, with a 1M-token context window. Benched via API the day it dropped; game tasks use our skill-infused AAA build prompts. |
| Release | 2026-05 | 2026-07 |
| Bench coverage | 47/47 scored · avg 7.51/10 | 13/22 scored · avg 5.60/10 |
The verdict — which should you pick?
Across 13 scored shared tasks, Opus 4.8 averaged 7.58/10, beating Claude Opus 5's 5.60/10 by 1.98 points. Pick Opus 4.8 when the build has to ship on the first prompt and you can afford the trade-offs in the comparison below.
If you only run one of these inside your stack, the head-to-head average above is the call. If you can run both, my honest play is to wire Opus 4.8 and Claude Opus 5 both into the Agent Operating System and dispatch each from the kanban by task type — mission-critical one-shot builds where 'has to work the first time' matters → Opus 4.8, hardest agentic builds → Claude Opus 5. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — Opus 4.8 vs Claude Opus 5
Which is better, Opus 4.8 or Claude Opus 5?
On Goldie Bench, Opus 4.8 averages 7.58/10 across the shared tasks, with 3 gold, 1 silver, 1 bronze overall. Claude Opus 5 averages 5.60/10, with 0 gold, 0 silver, 1 bronze. Opus 4.8 wins the head-to-head 9–4.
How much does Opus 4.8 cost vs Claude Opus 5?
Opus 4.8: Premium pricing via the Anthropic API: $15 per million input tokens, $75 per million output tokens. Extended thinking is included but adds latency. Claude Opus 5: Anthropic's brand-new flagship — the first Opus of the Claude 5 family, with a 1M-token context window. Benched via API the day it dropped; game tasks use our skill-infused AAA build prompts.
What's the context window for Opus 4.8 vs Claude Opus 5?
Opus 4.8 has a 200,000 tokens (1M with extended thinking) context window. Claude Opus 5 has a 1,000,000 tokens context window.
When should I pick Opus 4.8 over Claude Opus 5?
Pick Opus 4.8 for: Mission-critical one-shot builds where 'has to work the first time' matters; Hard reasoning tasks (planning, multi-step) where you'll pay for the depth; Anything where vendor reliability beats the per-token bill. The trade-off is the weaknesses we logged on the bench: 5–10× the per-token cost of every other model on the bench; Less flair on cinematic visuals than GLM-5.2 — playing it safer wins on accuracy, costs you on showpiece moments.
When should I pick Claude Opus 5 over Opus 4.8?
Pick Claude Opus 5 for: Hardest agentic builds; Whole-repo reasoning; Frontier one-shots. The trade-off is the weaknesses we logged on the bench: Premium pricing ($5/$25 per M) — route the everyday 90% to cheaper lanes; Reasoning-by-default eats token budgets unless tuned per call.
How does Goldie Bench score Opus 4.8 vs Claude Opus 5?
Every demo on this page was built by Julian Goldie inside the Agent Operating System — same fixed prompt for both models, one shot, single HTML file out. Each result gets a 0–10 score on whether it ran, how close it hit the brief, and how good it looked. The highest score on each task gets gold; second gets silver; third gets bronze. See methodology for full provenance.
Related comparisons
Other head-to-heads using the same scoring system:
Opus 4.8 vs Fusion Claude Opus 5 vs Fusion Opus 4.8 vs Hermes MoA Claude Opus 5 vs Hermes MoA Opus 4.8 vs GPT-5.6 Sol Claude Opus 5 vs GPT-5.6 Sol Opus 4.8 vs Claude Fable 5 Claude Opus 5 vs Claude Fable 5Full model pages: Opus 4.8 · Claude Opus 5 · back to the leaderboard
Run this stack yourself.
Every demo on this bench was built inside the Agent Operating System — one prompt, one shot, single HTML file out. The Agent OS, the prompts, the templates, the weekly walkthroughs and 4,000+ founders shipping with it every day all live inside the AI Profit Boardroom.



































