Real head-to-head · same prompt, one shot
MiniMax M3 vs Opus 4.8
1M-context frontier model at $0.30/M tokens — cheapest big-context model on the bench. vs The reasoning king — deepest thinking, premium price.
Head-to-head verdict: MiniMax M3 wins 27–14 with 6 ties.
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 MiniMax M3 and Opus 4.8, side by side, on 47 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.
MiniMax M3 · Bench prompts dispatched via OpenRouter. Scored by Claude judge against the same 42 prompts every other model ran.
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.
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 = 🥉).
Task ↓
MiniMax M3
Opus 4.8
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Page
Where MiniMax M3 beat Opus 4.8
The tasks where I gave MiniMax M3 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
Nordiccrypt
Game
MiniMax M3 9.0
·
Opus 4.8 6.0
(+3.0)
What I saw: 41KB Nordic crypt with torch-lit corridors, chasing skeletons, boss room.
Webos
Page
MiniMax M3 8.5
·
Opus 4.8 5.5
(+3.0)
What I saw: 38KB working desktop — wallpaper, dock, draggable Notes/Paint/Terminal/Calculator windows.
Crypt
Game
MiniMax M3 8.5
·
Opus 4.8 6.0
(+2.5)
What I saw: Nordic dungeon crawler on three.js — torch-lit corridors, skeletons.
Dragonrealm
Game
MiniMax M3 9.0
·
Opus 4.8 7.0
(+2.0)
· winner · biggest Dragon Realm
What I saw: 34KB frozen open world — snowy mountains, pines, flying dragon, full HUD.
Pool
Game
MiniMax M3 7.5
·
Opus 4.8 5.5
(+2.0)
What I saw: Canvas-2D billiards with 16 balls, pockets, click-drag aim.
Where Opus 4.8 beat MiniMax M3
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.
Blackhole
Sim
Opus 4.8 9.0
·
MiniMax M3 7.0
(+2.0)
· winner · hit the brief
What I saw: Opus nailed it — a pure-black event horizon, a bright photon ring, and the disk bent up and over the top exactly like the film's lensing. GLM came in strong with a clean ring and a starfield warping past the hole. Kimi's disk is fine, but the background is a soft grey blur instea…
Plasma
Visual
Opus 4.8 7.5
·
MiniMax M3 6.0
(+1.5)
What I saw: 5KB · plays clean · webgl, rAF
Galaxy
Sim
Opus 4.8 8.5
·
MiniMax M3 7.5
(+1.0)
· winner · interactive 3D
What I saw: Opus built a proper interactive 3D galaxy — drag to orbit a 7,000-star cloud around a glowing core. Kimi's is the prettiest single frame: a clean tilted spiral disk with rainbow arms. GLM's runs on a canvas with a slick NGC-style HUD and zoom, just less dramatic at a glance. Thre…
Landing
Page
Opus 4.8 9.0
·
MiniMax M3 8.0
(+1.0)
· tie · top
What I saw: Funniest result of the lot: GLM and Opus independently produced near-identical premium 'Introducing Nova 1 — Intelligence, reimagined / distilled' keynote pages — gradient hero, full nav, pricing tiers. A dead heat. Kimi's was a plainer set of feature cards.
Neoncity
Game
Opus 4.8 8.5
·
MiniMax M3 7.5
(+1.0)
What I saw: GLM's is the most cinematic — neon towers, a setting sun, Japanese signage and a flight HUD, like a frame from a film. Opus's is a clean canyon of lit skyscrapers racing to a vanishing point. Kimi leaned into the synthwave sun and grid more than the city itself. GLM wins the skyline.
Strengths & weaknesses I logged
MiniMax M3
Strengths
- 1M token context — full repo / full deep-research corpus fits in one call
- $0.30/M input is roughly 1/30th of Opus 4.8 — built for high-volume agent loops
- Solid one-shot HTML output — clean structure on game and visual prompts
Trade-offs
- Less polished than Fusion's panel-ensembled output on the toughest deep builds
- Newer model — less community calibration vs Fable 5 / Opus 4.8
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
Pricing & context — the spec sheet
| Spec | MiniMax M3 | Opus 4.8 |
|---|---|---|
| Vendor | MiniMax | Anthropic |
| Context window | 1,048,576-token context — matches GLM-5.2 and Fable 5 | 200,000 tokens (1M with extended thinking) |
| Price | $0.30 / 1M input tokens, $1.50 / 1M output | $15 / $75 per M tokens |
| Pricing detail | MiniMax M3 is the cheapest 1M-context frontier model on the bench — roughly 1/200th the per-call cost of OpenRouter Fusion and 1/30th of Claude Opus 4.8. Designed for high-volume agent workloads where context length matters but per-call budget is tight. | Premium pricing via the Anthropic API: $15 per million input tokens, $75 per million output tokens. Extended thinking is included but adds latency. |
| Release | 2026-06-18 | 2026-05 |
| Bench coverage | 47/47 scored · avg 7.97/10 | 47/47 scored · avg 7.51/10 |
The verdict — which should you pick?
Across 47 scored shared tasks, MiniMax M3 averaged 7.97/10, beating Opus 4.8's 7.51/10 by 0.46 points. Pick MiniMax M3 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 MiniMax M3 and Opus 4.8 both into the Agent Operating System and dispatch each from the kanban by task type — high-volume agent workflows where per-call cost dominates → MiniMax M3, mission-critical one-shot builds where 'has to work the first time' matters → Opus 4.8. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — MiniMax M3 vs Opus 4.8
Which is better, MiniMax M3 or Opus 4.8?
On Goldie Bench, MiniMax M3 averages 7.97/10 across the shared tasks, with 2 gold, 1 silver, 4 bronze overall. Opus 4.8 averages 7.51/10, with 3 gold, 1 silver, 1 bronze. MiniMax M3 wins the head-to-head 27–14.
How much does MiniMax M3 cost vs Opus 4.8?
MiniMax M3: MiniMax M3 is the cheapest 1M-context frontier model on the bench — roughly 1/200th the per-call cost of OpenRouter Fusion and 1/30th of Claude Opus 4.8. Designed for high-volume agent workloads where context length matters but per-call budget is tight. 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.
What's the context window for MiniMax M3 vs Opus 4.8?
MiniMax M3 has a 1,048,576-token context — matches GLM-5.2 and Fable 5 context window. Opus 4.8 has a 200,000 tokens (1M with extended thinking) context window.
When should I pick MiniMax M3 over Opus 4.8?
Pick MiniMax M3 for: High-volume agent workflows where per-call cost dominates; 1M-context tasks (whole-repo refactors, deep-research synthesis); Drop-in cheaper alternative to GLM-5.2 with comparable 1M context. The trade-off is the weaknesses we logged on the bench: Less polished than Fusion's panel-ensembled output on the toughest deep builds; Newer model — less community calibration vs Fable 5 / Opus 4.8.
When should I pick Opus 4.8 over MiniMax M3?
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.
How does Goldie Bench score MiniMax M3 vs Opus 4.8?
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:
MiniMax M3 vs Fusion Opus 4.8 vs Fusion MiniMax M3 vs Claude Opus 5 Opus 4.8 vs Claude Opus 5 MiniMax M3 vs Hermes MoA Opus 4.8 vs Hermes MoA MiniMax M3 vs GPT-5.6 Sol Opus 4.8 vs GPT-5.6 SolFull model pages: MiniMax M3 · Opus 4.8 · back to the leaderboard
The same stack Julian uses
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.
4,000+founders
258documented wins
38countries
$59/momonthly