
Real head-to-head · same prompt, one shot
Qwen 3.8 vs DeepSeek V4 Pro
Alibaba's 2.4T flagship — benched through Qoder. vs DeepSeek's flagship tier — benched head-to-head against its own cheap Flash.
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 Qwen 3.8 and DeepSeek V4 Pro, side by side, on 45 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.
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.
DeepSeek V4 Pro · Benched on all 50 GoldieBench tasks via api.deepseek.com with the same pipeline as the Flash 0731 run, then published as a live side-by-side: goldiebench.com/vs-live/deepseek-flash-vs-pro.html loads both builds of every task in twin panes.
Side-by-side on 50 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 ↓
Qwen 3.8
DeepSeek V4 Pro
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Game
Other
Other
Other
Page
Page
Page
Strengths & weaknesses I logged
Qwen 3.8
Strengths
- Skyrim-style open worlds — the Dragon Realm build rendered a lit snowfield, first-person sword and working roaming enemies (7.8)
- Held up across game genres early — voxel sandbox and Doom raycaster both came out shippable
- Runs as a real agentic coder inside Qoder (writes + iterates on files), not just a chat model
Trade-offs
- 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
DeepSeek V4 Pro
Strengths
- Flagship reasoning tier on the same official API and 1M context as Flash
- Ran the identical 50-prompt set as V4 Flash 0731 — a clean same-vendor A/B
- Reasoning-first: thinks before writing every build
Trade-offs
- Unranked — builds are on the bench but not yet scored by the Opus vision judge
- Slower and pricier per build than Flash — the whole question is whether that buys quality
Pricing & context — the spec sheet
| Spec | Qwen 3.8 | DeepSeek V4 Pro |
|---|---|---|
| Vendor | Alibaba | DeepSeek |
| Context window | Served through Alibaba's Qoder agent platform; the 3.8-Max preview has no standalone public context window yet. | 1,000,000-token context window |
| Price | Qoder plan | API · pro tier |
| Pricing detail | 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. | DeepSeek's flagship tier, benched on `deepseek-v4-pro` via api.deepseek.com — the exact same 50 one-shot prompts, skill-infused game prompt and pipeline as the V4 Flash 0731 run, so the two runs are directly comparable side by side. DeepSeek's own line on the 0731 Flash refresh is that its post-training now beats the older V4-Pro-Preview — this run tests the current Pro against that claim. |
| Release | 2026-07 | 2026-07 |
| Bench coverage | 45/45 scored · avg 8.10/10 | 0/50 scored · avg — |
The verdict — which should you pick?
Not enough scored shared tasks yet for a head-to-head average. The live demos for both are on the matrix above — play them and form your own opinion.
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 Qwen 3.8 and DeepSeek V4 Pro both into the Agent Operating System and dispatch each from the kanban by task type — one-shot 3d game and world prototypes where atmosphere matters → Qwen 3.8, checking whether deepseek's pro tier is worth the premium over flash 0731 → DeepSeek V4 Pro. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — Qwen 3.8 vs DeepSeek V4 Pro
Which is better, Qwen 3.8 or DeepSeek V4 Pro?
On Goldie Bench, Qwen 3.8 averages no scored verdicts yet across the shared tasks, with 8 gold, 7 silver, 7 bronze overall. DeepSeek V4 Pro averages no scored verdicts yet, with 0 gold, 0 silver, 0 bronze. Not enough scored shared tasks yet to call a winner.
How much does Qwen 3.8 cost vs DeepSeek V4 Pro?
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. DeepSeek V4 Pro: DeepSeek's flagship tier, benched on `deepseek-v4-pro` via api.deepseek.com — the exact same 50 one-shot prompts, skill-infused game prompt and pipeline as the V4 Flash 0731 run, so the two runs are directly comparable side by side. DeepSeek's own line on the 0731 Flash refresh is that its post-training now beats the older V4-Pro-Preview — this run tests the current Pro against that claim.
What's the context window for Qwen 3.8 vs DeepSeek V4 Pro?
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. DeepSeek V4 Pro has a 1,000,000-token context window context window.
When should I pick Qwen 3.8 over DeepSeek V4 Pro?
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.
When should I pick DeepSeek V4 Pro over Qwen 3.8?
Pick DeepSeek V4 Pro for: Checking whether DeepSeek's pro tier is worth the premium over Flash 0731; Hard single-shot builds where extra reasoning depth may pay off. The trade-off is the weaknesses we logged on the bench: Unranked — builds are on the bench but not yet scored by the Opus vision judge; Slower and pricier per build than Flash — the whole question is whether that buys quality.
How does Goldie Bench score Qwen 3.8 vs DeepSeek V4 Pro?
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:
Qwen 3.8 vs Fusion DeepSeek V4 Pro vs Fusion Qwen 3.8 vs Claude Opus 5 DeepSeek V4 Pro vs Claude Opus 5 Qwen 3.8 vs Hermes MoA DeepSeek V4 Pro vs Hermes MoA Qwen 3.8 vs GPT-5.6 Sol DeepSeek V4 Pro vs GPT-5.6 SolFull model pages: Qwen 3.8 · DeepSeek V4 Pro · 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














































