Choosing the Right Model for Your Project

Updated November 2, 2026 — Imagine. grok-imagine-image-quality was deprecated on November 2, 2026: its requests are now served by Imagine Image 2.0 (grok-imagine-image-2.0, $0.04 per image) at low quality. Replace the identifier in examples and set the desired quality; grok-imagine-image (version 1.0) is not affected. Imagine Image 2.0 accepts up to five reference images and the auto quality setting, which is now the default.

Summary and Decision Support

Now that you’ve explored every model in the Grok lineup, it’s time to synthesize that knowledge into a practical decision framework. This final lesson gives you a decision tree, recommendations by project type, and a summary of key points.

Decision Tree

The order of questions isn’t arbitrary: you eliminate the non-negotiable cases first (multimedia and code have their dedicated models), then decide on the rest. Follow them in order, and resist the urge to jump straight to budget—a cheap model that’s ill-suited always costs more than the right model once you count retries and corrections:

1. Does your task involve multimedia content?

• Image generation: grok-imagine-image (Imagine 1.0, $0.02) or grok-imagine-image-2.0 (Imagine 2.0, $0.04 at low quality)
• Video generation: grok-imagine-video ($0.05/s), grok-imagine-video-1.5 ($0.08/s), or grok-imagine-video-1.5-lite ($0.02/s)
• Voice interaction: Voice API (real-time voice agent)
• Voice synthesis or transcription: Text-to-Speech / Speech-to-Text
• No: go to question 2

2. Is your task primarily code?

• Yes, and speed is priority: grok-build-0.1 (the fastest code model in the lineup)
• Yes, but the problem is highly complex (architecture, deep debugging): grok-4.5 with high reasoning effort
• No: go to question 3

3. Does your task require complex reasoning?

• Yes (math, logic, multi-step analysis): grok-4.5 (configurable reasoning) or grok-4.20-0309-reasoning
• No (writing, summarization, classification): grok-4.3 or grok-4.20-0309-non-reasoning

4. What is your budget?

• Tight budget / high volume: grok-4.3 ($1.25 / $2.50 per M under 200k)
• Comfortable budget / maximum quality: grok-4.5 ($2.00 / $6.00 per M under 200k)

5. Do you need to orchestrate multiple agents?

• Yes: grok-4.20-multi-agent-0309
• No: the model identified in previous steps

Recommendations by Project Type

Pricing Summary

Reminder: beyond 200,000 context tokens, text model prices double (grok-4.5: $4.00 / $12.00; grok-4.3: $2.50 / $5.00).

Most Common Mistakes

Before wrapping up, here are the pitfalls to avoid:

1. Using grok-4.5 for everything — reserve it for tasks that really need it, otherwise costs explode.

2. Crossing the 200k threshold without knowing it — as soon as cumulative context exceeds 200,000 tokens, prices double. Monitor the size of your conversations and documents.

3. Neglecting input cache — a stable prompt prefix is billed at the cached rate ($0.20 to $0.30 per million depending on the model). Changing the start of your prompts on every request means paying full price unnecessarily.

4. Choosing the wrong reasoning effort — with grok-4.5, too high an effort slows down and increases the cost of simple tasks; too low an effort degrades complex tasks. Test several settings.

5. Using a model from a previous generation — Grok 3 (including grok-3-mini) and Grok 4 without suffix should no longer be used for new projects. Check the official models page for catalog status.

6. Not monitoring deprecations — a frozen version will eventually be removed. Plan your migrations in advance.

Pre-Deployment Checklist

Before putting your application into production with the Grok API, check these points:

• You are using a model identifier from the current catalog (not a deprecated generation)
• Your system prompt is stable to maximize input cache
• You know the typical size of your contexts and whether you cross the 200k threshold
• You have implemented exponential backoff for 429 errors
• You have calibrated reasoning effort (grok-4.5) or chosen the right variant (4.20 reasoning / non-reasoning)
• Your timeouts are sized for long responses with reasoning
• You have estimated your monthly costs based on the official pricing grid
• You have a migration plan for future versions

Pricing as of August 5, 2026 — prices change regularly: before any budget calculation, check the current grid on the official xAI models and pricing page.

Key Takeaways

• Use the decision tree: multimedia, code, reasoning, budget, multi-agent
• grok-4.3 is the default choice for most cases; grok-4.5 for maximum quality
• grok-build-0.1 for code, grok-4.20-multi-agent-0309 for agent orchestration
• Combine input cache + context under 200k + right model to optimize costs
• Avoid classic mistakes: wrong model, crossed context threshold, unused cache
• Always plan your version migrations in advance

Test Your Knowledge

The models guide: five questions to anchor the selection criteria.

1. How is the Grok model offering organized?

Answer: Tiered generalists (high-end, large-context economic option, 4.20 variants) and specialists: code (grok-build), image and video (grok-imagine), voice (Voice Agent, TTS).

2. Reasoning or non-reasoning: what's the practical difference?

Answer: Reasoning variants think before answering—better on complex problems, slower and more expensive; non-reasoning respond quickly for direct tasks.

3. What should you understand about naming conventions?

Answer: API identifiers carry the variant and dating—check the exact identifiers in effect (console/documentation) before any deployment, as the lineup evolves quickly.

4. What levers optimize your costs?

Answer: Choose the model to match exact needs, monitor token pricing and integrated tool costs, and reserve large contexts for cases that truly require them.

5. How do you choose the right model for a project?

Answer: By task: specialist if the domain requires it (code, image, voice); otherwise generalist, sized by requirement (reasoning?) and budget—then validate with a measured test.

The lineup changes, the criteria remain: task, requirement, budget, measured test—the course decision tree is your enduring tool.