Grok 4.6 vs Grok 4.5: Benchmarks, Cost and Upgrade Decision
xhigh reasoning option, higher cached-input price, and vendor-reported benchmark gains. Use the Grok 4.6 API page for its current EvoLink route and price; use this comparison to decide which workloads deserve a migration test.Quick comparison
| Decision factor | Grok 4.6 | Grok 4.5 | Routing implication |
|---|---|---|---|
| Model ID | grok-4.6 | grok-4.5 | Keep IDs in configuration, not application branches. |
| Context window | 500K | 500K | Context capacity alone is not an upgrade reason. |
| Reasoning effort | low, medium, high, xhigh | low, medium, high | Test xhigh only on tasks that justify more latency and usage. |
| Standard direct price per 1M | $2 input / $0.50 cached / $6 output | $2 input / $0.30 cached / $6 output | Repeated-context workloads may retain a cost advantage on 4.5. |
| Long-context direct price per 1M | $4 / $1 / $12 | $4 / $0.60 / $12 | Cached-input difference continues above the 200K threshold. |
| Best initial test | Hard coding, agents, visual or interactive builds | Stable existing Grok workloads | Promote by workload, not by model age. |
What actually changed
xAI describes Grok 4.6 as a re-engineered model trained with agentic reinforcement learning to remain effective across longer tasks, research unfamiliar codebases, create structure, implement features, and self-test its work. These are vendor claims that define good evaluation targets; they are not a substitute for testing your repositories, tools, review rules, and latency budget.
Grok 4.5 remains a capable production baseline for coding, agentic tasks, and knowledge work. If it already meets an SLO, the migration question is not “is 4.6 newer?” but “does 4.6 reduce failed work, retries, tool loops, or reviewer correction enough to offset any additional usage?”
How to read the official benchmarks
xAI reports gains for Grok 4.6 over Grok 4.5 on several evaluations, including CursorBench, DeepSWE, FrontierCode, Artificial Analysis, and GDPVal. The published examples include 69.9 versus 66.7 on CursorBench and 65.9 versus 54.0 on DeepSWE. Treat these as attributed vendor results: useful for choosing test workloads, but not proof that every codebase or agent harness will see the same gain.
| Benchmark question | Safe interpretation | Production follow-up |
|---|---|---|
| Does 4.6 score higher in the launch report? | Yes, on the vendor's published comparison. | Reproduce the closest workload with your own harness. |
| Does that prove lower production cost? | No. Scores do not include your retries, tools, or review time. | Measure cost per accepted task. |
| Does it prove 4.5 should be retired? | No. Existing traffic may not benefit equally. | Segment traffic and canary only likely winners. |
Cost is not identical
The direct standard input and output prices are the same, but prompt caching is not. Grok 4.6 lists $0.50 per million cached input tokens below 200K prompt input, while Grok 4.5 lists $0.30. For repository agents and long conversations with stable prefixes, that difference can matter. EvoLink route prices may differ from direct list prices, so compare the live price modules and actual usage for the channel you deploy.
Use this production cost model:
accepted_task_cost = input + cached_input + output + tool_calls
+ retries + fallback_calls + reviewer_timeWhich workloads should move first?
| Workload | Recommended starting route | Promotion rule |
|---|---|---|
| Unfamiliar repository feature work | Grok 4.6 shadow test | Promote when complete-change rate and test pass rate improve. |
| Long-running tool agent | Paired 4.5/4.6 replay | Promote when loops and human intervention fall. |
| Visual frontend implementation | Grok 4.6 evaluation | Validate responsive behavior, accessibility, and design-system compliance. |
| Stable chat or extraction | Keep Grok 4.5 initially | Move only if quality or total cost improves. |
| Cache-heavy long sessions | Compare both at the same context budget | Include cached-input rate and cache-hit reliability. |
A safe upgrade plan on EvoLink
- Keep
grok-4.5as the rollback route. - Replay 20–50 representative tasks against
grok-4.6with the same context and tools. - Record accepted output, latency, token mix, tool calls, retries, and reviewer correction.
- Run shadow traffic before exposing 4.6 output to users.
- Canary only the workload classes where 4.6 wins.
- Roll back on identity, reliability, cost, or critical-quality regression.
EvoLink reduces provider-integration overhead by keeping model evaluation behind one gateway, but model-specific behavior still needs explicit acceptance tests.
FAQ
Is Grok 4.6 better than Grok 4.5?
xAI reports higher 4.6 results across several coding and agent evaluations. Whether it is better for your system depends on matched workload tests, tool reliability, latency, and accepted-task cost.
Do Grok 4.6 and Grok 4.5 use the same model ID?
grok-4.6 and grok-4.5 respectively.Are the prices identical?
Standard direct input and output rates match, but cached-input rates differ. Check the live EvoLink price for the route and user group you will use.
Do both models have 500K context?
Yes. Both official model pages document a 500,000-token context window.
Should existing Grok 4.5 applications switch immediately?
No. Start with replay, shadow traffic, and a small workload-specific canary while keeping a tested fallback.
What should teams measure during migration?
Measure task acceptance, latency, input/cache/output tokens, tool-call success, retries, human correction, and total cost per accepted task.
