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Real head-to-head · same prompt, one shot

Inkling vs DeepSeek V4 Pro

A 975B open-weights frontier model — yours to own and run. vs DeepSeek's flagship tier — benched head-to-head against its own cheap Flash.

Inkling · context1M tokens
DeepSeek V4 Pro · context1M tokens
Inkling · price$0.33 / M
DeepSeek V4 Pro · priceAPI · pro tier
Inkling · vendorThinking Machines
DeepSeek V4 Pro · vendorDeepSeek

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 Inkling and DeepSeek V4 Pro, side by side, on 50 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.

Inkling · Benched on GoldieBench one-shot through Tinker's OpenAI-compatible endpoint at medium reasoning effort, then headless-playtested on the same rubric as the whole field. In the Agent OS it's wired into the opencode tab on your own Tinker key — the Ink Machine.

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 ↓
Inkling
DeepSeek V4 Pro
Game
Inkling on Arcade
DeepSeek V4 Pro on Arcade
Game
Inkling on Crypt
DeepSeek V4 Pro on Crypt
Game
Inkling on Dogfight
DeepSeek V4 Pro on Dogfight
Game
Inkling on Doom
DeepSeek V4 Pro on Doom
Inkling on Dragonflight
DeepSeek V4 Pro on Dragonflight
Inkling on Dragonrealm
DeepSeek V4 Pro on Dragonrealm
Game
Inkling on Flightsim
DeepSeek V4 Pro on Flightsim
Game
Inkling on Game
DeepSeek V4 Pro on Game
Game
Inkling on Gtadrive
DeepSeek V4 Pro on Gtadrive
Game
Inkling on Gtafoot
DeepSeek V4 Pro on Gtafoot
Inkling on Neonblaster
DeepSeek V4 Pro on Neonblaster
Game
Inkling on Neoncity
DeepSeek V4 Pro on Neoncity
Game
Inkling on Neonracer
DeepSeek V4 Pro on Neonracer
Inkling on Nordiccrypt
DeepSeek V4 Pro on Nordiccrypt
Game
Inkling on Outrun
DeepSeek V4 Pro on Outrun
Game
Inkling on Parachute
DeepSeek V4 Pro on Parachute
Game
Inkling on Pool
DeepSeek V4 Pro on Pool
Game
Inkling on Racing
DeepSeek V4 Pro on Racing
Game
Inkling on Raycaster
DeepSeek V4 Pro on Raycaster
Game
Inkling on Rpg
DeepSeek V4 Pro on Rpg
Game
Inkling on Skyrim
DeepSeek V4 Pro on Skyrim
Inkling on Twilightvale
DeepSeek V4 Pro on Twilightvale
Game
Inkling on Voxelcraft
DeepSeek V4 Pro on Voxelcraft
Other
Inkling on Matrixrain
DeepSeek V4 Pro on Matrixrain

Strengths & weaknesses I logged

Inkling

Strengths

  • Genuinely open-weights — the full 975B model is public on Hugging Face; run it on your own key, no black box
  • Best one-shot builds are 2D / animation / web — a matrix-rain that topped its task (8.4), plus arcade, fractal, aurora and a mini web-OS all judged shippable (7.6–8.2)
  • Frontier-class agentic coding for an open model — 77.6% SWE-bench Verified, ahead of Nemotron 3 Ultra
  • 1M-token context, native multimodal (text/image/audio), and a controllable thinking-effort dial

Trade-offs

  • One-shot 3D games are weak — three.js dungeons/racers render a title screen but no playable scene, like most open models (crypt 2.5)
  • Physics and particle sims are hit-or-miss — black-hole, plasma and cloth one-shots often render dark or static (2.3–3.5)
  • Not the strongest overall — the closed frontier (Fable 5) still tops the raw benchmarks; Inkling trades peak for ownership

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 Inkling DeepSeek V4 Pro
VendorThinking MachinesDeepSeek
Context window1,000,000 tokens1,000,000-token context window
Price$0.33 / MAPI · pro tier
Pricing detailInkling is open-weights — a 975B-parameter (41B active) Mixture-of-Experts model whose full weights are public on Hugging Face. You run it on your own key through Tinker's OpenAI-compatible endpoint (usage-based, ~$0.33/M sampling, 50% off at launch), or via Together / Fireworks / Modal / Databricks / Baseten. Benched here one-shot at medium reasoning effort via Tinker.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.
Release2026-072026-07
Bench coverage50/50 scored · avg 6.07/100/50 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 Inkling and DeepSeek V4 Pro both into the Agent Operating System and dispatch each from the kanban by task type — owning a frontier model instead of renting one — on your own key, pennies per build → Inkling, 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 — Inkling vs DeepSeek V4 Pro

Which is better, Inkling or DeepSeek V4 Pro?

On Goldie Bench, Inkling averages no scored verdicts yet across the shared tasks, with 0 gold, 0 silver, 0 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 Inkling cost vs DeepSeek V4 Pro?

Inkling: Inkling is open-weights — a 975B-parameter (41B active) Mixture-of-Experts model whose full weights are public on Hugging Face. You run it on your own key through Tinker's OpenAI-compatible endpoint (usage-based, ~$0.33/M sampling, 50% off at launch), or via Together / Fireworks / Modal / Databricks / Baseten. Benched here one-shot at medium reasoning effort via Tinker. 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 Inkling vs DeepSeek V4 Pro?

Inkling has a 1,000,000 tokens context window. DeepSeek V4 Pro has a 1,000,000-token context window context window.

When should I pick Inkling over DeepSeek V4 Pro?

Pick Inkling for: Owning a frontier model instead of renting one — on your own key, pennies per build; Generative visuals, data-viz and single-file web builds you want one-shot; A customizable open base you can fine-tune on Tinker for your own domain. The trade-off is the weaknesses we logged on the bench: One-shot 3D games are weak — three.js dungeons/racers render a title screen but no playable scene, like most open models (crypt 2.5); Physics and particle sims are hit-or-miss — black-hole, plasma and cloth one-shots often render dark or static (2.3–3.5); Not the strongest overall — the closed frontier (Fable 5) still tops the raw benchmarks; Inkling trades peak for ownership.

When should I pick DeepSeek V4 Pro over Inkling?

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 Inkling 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.

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.

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