GPT-5.6 Sol vs Qwen 3.8

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 GPT-5.6 Sol and Qwen 3.8, side by side, on 41 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.

GPT-5.6 Sol · Benched on GoldieBench as the flagship Sol at medium reasoning, one-shot, then headless-playtested. In the Agent OS it's the top tier of a routed stack — Sol on the hard calls, Terra for the bulk, Luna for the everyday 90%.

Qwen 3.8 · Benched on GoldieBench via the Qoder CLI (`qoder-qwen`, model Qwen3.8-Max-Preview) — the only door while it has no public API. Non-game tasks are one-shot like the rest of the field. GAME tasks run in Qoder's real AGENT mode: skill-infused build, then up to 2 QA fix rounds where a vision judge + live console errors are fed back and Qwen 3.8 edits its own file (it took crypt from a black-screen 3.0 to a torch-lit 7.8). Scored on a mid-play frame by the same Opus judge as everyone else. This is a partial run — the full 50-task card replaces it when the batch completes.

Where GPT-5.6 Sol beat Qwen 3.8

The tasks where I gave GPT-5.6 Sol a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Where Qwen 3.8 beat GPT-5.6 Sol

The tasks where I gave Qwen 3.8 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Strengths & weaknesses I logged

Pricing & context — the spec sheet

The verdict — which should you pick?

Across 41 scored shared tasks, the averages are essentially tied — GPT-5.6 Sol 8.23 vs Qwen 3.8 8.22. This isn't the comparison where one wins; it's the comparison where you pick based on context, pricing, and what you're actually trying to ship.

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 GPT-5.6 Sol and Qwen 3.8 both into the Agent Operating System and dispatch each from the kanban by task type — the hardest reasoning and code where being right beats being cheap → GPT-5.6 Sol, one-shot 3d game and world prototypes where atmosphere matters → Qwen 3.8. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — GPT-5.6 Sol vs Qwen 3.8

Which is better, GPT-5.6 Sol or Qwen 3.8?

On Goldie Bench, GPT-5.6 Sol averages 8.23/10 across the shared tasks, with 6 gold, 11 silver, 7 bronze overall. Qwen 3.8 averages 8.22/10, with 10 gold, 9 silver, 5 bronze. It's a curated tie on the head-to-head.

How much does GPT-5.6 Sol cost vs Qwen 3.8?

GPT-5.6 Sol: GPT-5.6 shipped as three models — Luna ($1/$6 per M), Terra ($2.50/$15) and Sol ($5/$30) — each with a same-price pro variant that ships a higher default reasoning effort. All share a ~1.05M-token context window and are rated High capability. Benched here on the flagship, Sol, at medium reasoning effort via OpenRouter. Qwen 3.8: Qwen3.8-Max-Preview is Alibaba's ~2.4T-parameter flagship, positioned just behind Claude Fable 5. It is NOT on OpenRouter or a public API yet — the only access today is inside Qoder (Alibaba's agentic coding platform, free 2-week Pro trial). Benched here via the Qoder CLI on model `Qwen3.8-Max-Preview`, one-shot.

What's the context window for GPT-5.6 Sol vs Qwen 3.8?

GPT-5.6 Sol has a 1,050,000 tokens context window. Qwen 3.8 has a Served through Alibaba's Qoder agent platform; the 3.8-Max preview has no standalone public context window yet. context window.

When should I pick GPT-5.6 Sol over Qwen 3.8?

Pick GPT-5.6 Sol for: The hardest reasoning and code where being right beats being cheap; One-shot game/sim prototypes you want shippable on the first prompt; The flagship slot in a routed Agent OS — Sol for the hard 10%, Luna/Terra for the rest. The trade-off is the weaknesses we logged on the bench: Priciest tier on the bench at $30/M output — only worth routing the hardest 10% of work to Sol; Reasoning can eat the token budget on big open-world briefs (one 0-byte failure until the budget was raised, then it built clean).

When should I pick Qwen 3.8 over GPT-5.6 Sol?

Pick Qwen 3.8 for: One-shot 3D game and world prototypes where atmosphere matters; Anyone already in the Qoder IDE/CLI wanting a near-frontier model free on the Pro trial; A cheaper stand-in for Fable 5 on creative-visual builds. The trade-off is the weaknesses we logged on the bench: Torch-lit dungeon (crypt) came out generic (6.3); one open-world RPG one-shot black-screened (twilightvale 2.5) — classic three.js r128 API drift; Preview is Qoder / Token-Plan only — no OpenRouter or public API, so it can't be routed into an app the way the OpenRouter models can.

How does Goldie Bench score GPT-5.6 Sol vs Qwen 3.8?

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:

Full model pages: GPT-5.6 Sol · Qwen 3.8 · back to the leaderboard