Grok 4.6 vs Opus 5: Which Model Is Better for Coding Agents?

AI Takeaway

• Which is better overall? Grok 4.6 is the stronger value pick for cost-sensitive coding-agent work. Claude Opus 5 is the better starting point when 1M context, Claude-native tooling, or judgment-heavy review matters more than price.
• Which is better for coding? On CursorBench 3.2, Grok 4.6 Extra High scored 70.8% at $2.81 per task, versus Opus 5 Max at 70.0% and $8.23. The score gap is too small for a universal verdict; the cost gap is more useful.
• Which is cheaper? Grok 4.6 costs $2/$6 per million input/output tokens, versus $5/$25 for Opus 5. Grok’s rates double beyond 200K context but remain below Opus 5’s base rates.
• Which has more context? Opus 5 offers 1M tokens, twice Grok 4.6’s 500K window.
• How should you choose? Run the same measurable task with the same files, tools, permissions, effort budget, and finish line. Pick the model that leaves less cost and cleanup.

Grok 4.6 vs Claude Opus 5 at a Glance

Grok 4.6 and Claude Opus 5 target much of the same high-value work: coding, multi-step agents, research, and complex knowledge tasks. Their biggest practical differences are price, context capacity, and the products around each model.

Category	Grok 4.6	Claude Opus 5
Provider	xAI	Anthropic
Main position	Coding, agentic tasks, and knowledge work	Complex agentic coding and enterprise work
API input	$2 / 1M tokens	$5 / 1M tokens
API output	$6 / 1M tokens	$25 / 1M tokens
Long-context rule	At 200K+: $4 input / $12 output	Standard listed rates across the 1M window
Context window	500K tokens	1M tokens
Input and output	Text and image input; text output	Text and image input; text output
Main ecosystem	Grok Build, Cursor, xAI API, and partners	Claude, Claude Code, Claude API, and cloud platforms

Separate the model from the runtime. Grok Build, Cursor, and Claude Code add their own tools, prompts, and context management. The AI coding-agent use case shows what persistent repository work requires: repo context, terminal access, tests, GitHub workflows, and an available workspace.

Which Model Is Better for Coding and Agent Work?

CursorBench Shows a Close Score and a Large Cost Gap

CursorBench 3.2 evaluates ambiguous, multi-file tasks from real Cursor sessions, making it more useful than a one-shot coding test.

Grok 4.6 Extra High scored 70.8%, used 46 steps, and cost an average of $2.81 per task. Opus 5 Max scored 70.0%, used 78 steps, and cost $8.23. At the High setting, Grok scored 69.9% at $2.34, while Opus scored 66.7% at $3.91.

Those results favor Grok on value, but do not prove that a 0.8-point lead will hold elsewhere. Cursor warns that small differences may not be statistically meaningful, and Extra High and Max may represent different compute budgets. The defensible takeaway is comparable performance with fewer steps and lower measured cost in this environment.

Grok 4.6 Favors Fast, Cost-Efficient Iteration

Grok 4.6 is the practical first choice for implementing features, running tests, correcting UI details, or processing similar coding tasks. Its low rates leave more room for tool calls and retries.

xAI also designed the model for long-running agents and visual or interactive projects. For frontend-heavy trials, the Playwright skill can give both models the same E2E tests, traces, and visual checks. The evidence supports strong coding-agent value, not superiority on every task.

Opus 5 Favors Deep Context and Careful Review

Opus 5 has the specification advantage beyond 500K tokens. Its 1M window can hold a larger repository or archive before compaction.

Anthropic positions Opus 5 around complex coding, verification, and careful iteration. It suits architecture review, root-cause analysis, and Claude Code workflows. The Claude Opus 5 review covers its access and limits.

The premium makes sense when a missed dependency would cost more than the run. For routine implementation, Grok’s price advantage is harder to ignore.

The Harness Can Change the Winner

Prompts, tools, context strategy, retries, and verification all affect whether a task finishes. The model supplies reasoning; the runtime determines what it can inspect and change.

Hold that tool surface constant. For issues, pull requests, or build failures, the GitHub skill gives both runs the same interface for PRs and CI results.

Reasoning labels are not directly comparable. A fair test must hold the environment constant and compare accepted outcomes, not brand labels.

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Pricing and Context: Is Opus 5 Worth the Premium?

API Token Prices and the 200K Grok Surcharge

At standard rates, Grok 4.6 is 60% cheaper on input and 76% cheaper on output. It also charges $0.50 per million cached input tokens.

Grok’s pricing changes once the prompt reaches 200K tokens. The full request then moves to $4 per million input tokens, $1 for cached input, and $12 for output. Even at those rates, it remains cheaper per token than Opus 5 at $5 input and $25 output.

Opus 5 costs more, but its 1M context window is available at its listed standard rates. If your workflow regularly crosses Grok’s threshold or exceeds 500K entirely, the price comparison becomes less dramatic and Opus gains a functional advantage.

Cost per Accepted Task Matters More Than Price per Token

The useful calculation is:

Cost per accepted task = model tokens + retries + tools and runtime + human correction time

A more expensive model can be cheaper if it finds the root cause and avoids rework. Grok’s CursorBench result shows the reverse: the lower-priced model completed comparable tasks with fewer steps. Across premium model comparisons, the finished task is a better unit of value than tokens alone.

Track pass rate, retries, elapsed time, and cleanup alongside the API bill. A cheap run that leaves broken tests is not cheap. A premium run that saves hours of review may be.

500K vs 1M Context: When the Difference Is Real

Opus 5 wins the context specification. The extra capacity matters for very large monorepos, long financial or legal archives, and multi-document research where aggressive trimming could remove important relationships.

Most tasks do not need a million-token prompt. Loading everything can raise cost and bury relevant evidence. File search, selective retrieval, compaction, and deliberate navigation often beat filling the window. Choose Opus when you can name the material that requires its extra headroom.

Choose Grok 4.6 or Opus 5 by Workload

Workload	Better starting point	Why
Repeated implementation and test cycles	Grok 4.6	Lower token and measured task cost leave more room for iteration
Large repositories or document sets above 500K	Opus 5	Its 1M context window provides the required headroom
Routine UI work and application prototyping	Grok 4.6	Strong shared coding result with lower cost per run
Architecture, root-cause review, or high-stakes analysis	Opus 5	Careful verification may justify the premium
Expensive work that benefits from independent review	Use both	Let one implement and the other challenge the plan or diff

The model is only one layer of the decision. The best AI agent for coding guide helps distinguish IDE assistance, terminal agents, GitHub workflows, and persistent coding automation. Use a second model only when independent review reduces more risk than it adds in time and cost.

Test Grok 4.6 and Opus 5 in the Same MyClaw Agent

A valid comparison needs the same runtime. MyClaw’s managed OpenClaw hosting provides a private, always-on agent environment where files, tools, skills, and workflow rules can remain consistent between runs. Confirm that both model IDs are available through your workspace or compatible provider before testing.

Step 1: Define One Scorable Agent Task

Choose a real finish line: make three named tests pass without changing the public API, or reproduce and fix one frontend bug against a fixed test case.

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Step 2: Hold the Runtime Constant

Give both runs the same base revision, files, tools, permissions, prompt, and time budget. Start clean and match reasoning effort as closely as each provider allows.

Step 3: Score the Work Left Behind

Record pass/fail, total cost, steps, retries, elapsed time, and manual corrections. Score only the accepted result. The better model is the one that leaves the smaller cleanup bill, not the more polished explanation.

Final Verdict: Grok 4.6 Wins on Value; Opus 5 Wins on Headroom

Choose Grok 4.6 first for coding-agent value, repeated runs, and cost-aware iteration. Choose Opus 5 when twice the context, Claude-native workflows, or careful judgment justifies the premium.

The public shared benchmark is close enough that neither model earns a universal crown. Use it to choose a starting point, then test the recurring task that actually affects your budget and output. The winner is the model that reaches an accepted result with fewer expensive surprises.