Model comparison
GPT-5.6 Sol vs Grok 4.6
GPT-5.6 Sol costs $4.00 / $20.00 and Grok 4.6 $2.00 / $6.00 per 1M input / output tokens. Both accept about 1M tokens of context, text, images and files.
GPT-5.6 Sol: sources list different prices. We use $4.00 / $20.00; OpenRouter shows $2.00 / $10.00. See every source.
Which one to choose
Picked by a published rule, not by an editor. Scenarios without data are left out.
Everyday requests
Grok 4.6
$0.014 vs $0.005 for 1,000 input and 500 output tokens.
Long prompts
Grok 4.6
A 500K-token prompt with a 2K-token answer costs $4.06 on GPT-5.6 Sol and $2.02 on Grok 4.6.
Context window
GPT-5.6 Sol
GPT-5.6 Sol: 1.05M tokens; Grok 4.6: 500K. Differences under 10% count as a tie.
How the verdicts are calculated
- Everyday requests: lower cost for 1,000 input + 500 output tokens at standard rates.
- Long prompts: lower cost for a 500K-token prompt and 2K-token answer, including long-context surcharges.
- Context window: bigger window wins; differences under 10% count as a tie.
- Mixed inputs: more input types accepted; a tie is not shown until multimodal benchmark scores are collected.
Not shown yet
- Coding: needs SWE-bench Verified scores
- Speed: needs independent output-speed measurements
- Privacy: needs data-retention and training-use policies
Side by side
The better value in each row is marked. Observed from LiteLLM and OpenRouter, checked against vendor pricing pages.
| Spec | GPT-5.6 Sol | Grok 4.6 |
|---|---|---|
| Input priceper 1M tokens | $4.00 | $2.00 (better) |
| Output priceper 1M tokens | $20.00 | $6.00 (better) |
| Cached inputper 1M tokens | $0.40 (better) | $0.50 |
| Typical request1,000 input + 500 output tokens | $0.014 | $0.005 (better) |
| Long-prompt pricingCompared on a 500K-token prompt | $8.00 / $30.00 above 272K tokens | $4.00 / $12.00 above 200K tokens (better) |
| Batch priceinput / output per 1M tokens | $2.00 / $10.00 | — |
| Context window | 1.05M tokens (better) | 500K tokens |
| Max output | 128K tokens | 450K tokens (better) |
| Knowledge cutoff | Feb 2026 | Not disclosed |
| Input types | Text, Images, Files (PDF) | Text, Images, Files (PDF) |
| Reasoning | Adjustable effort (better) | Always on |
| Tool use | Yes | Yes |
| Structured output (JSON) | Yes | Yes |
| BenchmarksGPQA Diamond, SWE-bench Verified, AIME 2025, LMArena | Not collected yet | Not collected yet |
| Output speedtokens per second | Not collected yet | Not collected yet |