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Midjourney Version 4 was an alpha test that began on November 5, 2022—not a current Midjourney model. In testing reported on November 9, V4 produced substantially more detailed and coherent images than Version 3, followed prompts more effectively, and sometimes generated unusually convincing proportions and photorealistic-looking scenes. The improvement was so accessible that some users called it “too easy.”
That phrase captured the central tension: V4 lowered the skill threshold for making an attractive image, while leaving open the question of how much creative authorship remained with the person writing the prompt.
What Midjourney Version 4 changed
Midjourney’s Version 4 was a new image model made available to subscribers through the company’s Discord workflow. The release came only a few months after Version 3 became Midjourney’s default model in August 2022, during the service’s rapid rise following its public opening in March.
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Ars Technica’s side-by-side testing found a noticeable step up from V3 in several practical areas:
- Detail: surfaces, clothing, faces, textures, and backgrounds could appear more resolved.
- Prompt comprehension: V4 was better at interpreting natural-language descriptions.
- Composition: multiple objects and characters were more likely to occupy a coherent scene.
- Proportions: subjects were sometimes more anatomically or geometrically plausible.
- Visual realism: some lower-resolution outputs could be difficult to distinguish from photographs at a glance.
These were observations from Ars’s testing, not a standardized benchmark. Midjourney separately described V4 as having broader visual knowledge, improved small details, stronger multi-object and multi-character handling, image prompting, multi-prompts, and support for the --chaos parameter.
Midjourney founder David Holz described V4 as an entirely new codebase and AI architecture trained on a new Midjourney supercluster after more than nine months of work. Those are company statements, not independently verified measurements. See the original Ars Technica report and Midjourney’s later legacy-model documentation.
Why users said V4 was “too easy”
The phrase was a community reaction, not a technical rating or an agreed consensus. Users could enter a short prompt such as “close-up photography of a face” and receive an image that already looked polished enough to share.
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For artists, that raised an uncomfortable question. If the model supplied the composition, lighting, palette, lens choice, styling, and much of the visual polish, what part of the result belonged to the person prompting it?
The concern did not mean that image generation required no judgment. Choosing a subject, revising a prompt, selecting among variations, correcting failures, and developing a distinctive visual direction still required taste. But V4 sharply reduced the effort needed to cross the first threshold from “rough experiment” to “convincing image.”
That is why the debate was about more than image quality. V4 made generative art more approachable, but it also made prompting feel less like a specialized craft. A short-lived joke about “prompt engineer” jobs reflected that anxiety, although the discussion was anecdotal rather than representative polling.
How the 2022 V4 alpha worked
In November 2022, subscribers could test the model through Midjourney’s Discord bot by adding --v 4 to an /imagine prompt. The example reported at the time was:
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/imagine a muscular barbarian with weapons beside a CRT television set, cinematic, 8K, studio lighting --v 4
The important qualification is the date. This was the historical Discord access method for the V4 alpha; it should not be treated as the current Midjourney interface or as a guarantee that the same command works today. Midjourney now identifies V4 as a legacy model.
V3 versus V4: the practical difference
| Area | What V4 appeared to improve | What the improvement did not guarantee |
|---|---|---|
| Prompt following | More of the requested objects and relationships appeared in the result. | Long or competing instructions could still be ignored. |
| Composition | Scenes with several objects or characters were more coherent. | Characters could still merge or exchange attributes. |
| Detail | Faces, materials, clothing, and backgrounds could look more finished. | Fine detail could still contain visual errors. |
| Anatomy and geometry | Proportions were sometimes better than in V3. | Hands, limbs, faces, and objects were not reliably correct. |
| Realism | Some low-resolution images looked convincingly photographic. | Plausible appearance did not establish factual accuracy or make an image a photograph. |
What was still unfinished
V4 was explicitly an alpha model. Midjourney expected further work on upscaled-image resolution and quality, image sharpness, custom aspect ratios, and text artifacts. These were planned improvements, not promises that every issue would be fixed on a particular schedule.
Text remained a particularly visible weakness. A generated sign, book cover, logo, or label might look convincing from a distance while containing invented lettering. The same applied to complex scenes: a model could produce a visually persuasive image whose objects were semantically wrong, physically impossible, or arranged in ways the prompt did not request.
Early community discussion also suggested that V4’s stronger model prior could feel more cartoony or stylistically different from Midjourney’s earlier “house style.” That reaction was subjective and should not be treated as a measured defect.
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The trade-off: ease versus control
V4’s strength was also its limitation. A strong model prior could turn a vague prompt into an attractive result, but it could also impose a recognizable Midjourney look or override unusual instructions.
- Ease versus authorship: better defaults helped beginners while making the creator’s contribution harder to define.
- Realism versus reliability: realistic-looking output increased the risk that synthetic images would be mistaken for documentary photographs.
- Coherence versus originality: knowledge of common visual patterns produced polished images, but sometimes conventional ones.
- Quality versus control: a pleasing result was not the same as precise control over every element.
- Iteration versus cost: finding a strong result often required generating and selecting from many variations.
For professional work, V4 was therefore better understood as an ideation and image-making tool than as a reliable replacement for a camera, illustrator, retoucher, or layout program. Copyright, consent, likeness, and commercial-use questions also remained separate from the model’s visual quality and depended on applicable law and Midjourney’s terms.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why the release mattered in 2022
Midjourney was one of the first widely visible public image-synthesis services. Its work was appearing in art contests, online communities, and debates over copyright and stock imagery. DALL-E and Stable Diffusion were important contemporaries, but they differed in access, workflows, control, training approaches, and visual character.
V4 mattered because it made high-quality results accessible to people who did not have specialist prompting experience. The breakthrough was not simply that the pictures were prettier. The system was increasingly able to infer what a user meant and supply the visual decisions needed to make the request look intentional.
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What happened after V4
Midjourney’s version history places V4’s release in November 2022. It became the default model from December 20, 2022, through March 30, 2023. Later milestones included V6 in December 2023, V7 in April 2025, and V8.1, released April 30, 2026 and made the default on June 10, 2026, according to Midjourney’s current documentation.
That history matters when reading older coverage. A screenshot, prompt recipe, subscription price, or assessment of image quality from the V4 period describes a particular moment in a rapidly changing product—not Midjourney as it exists now.
Historical alternatives and current options
In 2022, readers comparing Midjourney would commonly have looked at DALL-E and Stable Diffusion. Today, the best alternative depends on the workflow:
- Adobe Firefly suits users who want generative tools integrated with Creative Cloud.
- OpenAI image generation suits conversational and application-integrated workflows.
- Stability AI suits users who prioritize experimentation, ecosystem flexibility, or technical control.
- Canva AI suits social graphics, presentations, and templated marketing work.
Current prices, licensing terms, privacy rules, and model availability change over time. The $10–$50 monthly range reported by Ars in November 2022 should not be confused with current Midjourney pricing or usage rights.
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