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GPT-6.1 Sol vs GPT-4.1
A straight cost comparison of GPT-6.1 Sol (OpenAI) and GPT-4.1 (OpenAI), per 1,000,000 tokens, verified October 2026.
Rate-by-rate comparison
| Metric | GPT-6.1 Sol | GPT-4.1 | Winner |
|---|---|---|---|
| Input / 1M | $2 | $2 | Tie |
| Cached input / 1M | $0.10 | $0.50 | GPT-6.1 Sol |
| Cache write / 1M | $2.50 | — | GPT-4.1 |
| Output / 1M | $10 | $8 | GPT-4.1 |
| Context window | 1,050,000 | 1,047,576 | GPT-6.1 Sol |
| Batch API | Yes | Yes | Tie |
| Long-context tier | > 272,000 | None | — |
For per-token metrics, the lower number wins. For context window and batch support, the higher or broader option wins. A dash means the provider does not publish that rate: a missing cache-write fee means writes are not billed per token, while a missing cached-input rate means cache hits bill at the full input rate.
Blended cost: 1M input + 250K output
| Model | Blended cost | Difference |
|---|---|---|
| GPT-6.1 Sol | $4.50 | +$0.50 |
| GPT-4.1 | $4 | Cheaper |
Three workloads, two bills
| Workload | GPT-6.1 Sol | GPT-4.1 | Winner |
|---|---|---|---|
| Support chat 1,000 requests · 4K input / 600 output | $14 | $12.80 | GPT-4.1 |
| RAG with caching 1,000 requests · 50K input (45K cached) / 1K output | $24.61 | $40.57 | GPT-6.1 Sol |
| Nightly batch job 10,000 requests · 10K input / 2K output | $200 | $180 | GPT-4.1 |
Which one should you pick?
GPT-6.1 Sol wins on cached RAG, while GPT-4.1 wins on support chat, nightly batch job.
Beyond price, the two differ on output rate ($10 vs $8); cached-input rate ($0.10 vs $0.50); cache-write rate ($2.50 vs —); context window (1,050,000 vs 1,047,576); long-context tier (yes, above 272,000 vs none).
Batch mode is available on GPT-6.1 Sol and GPT-4.1, which halves the nightly job. Both publish cached-input discounts, so a stable system prompt is worth caching on either.
FAQ
Is GPT-6.1 Sol cheaper than GPT-4.1?
On a blended 1M-input-plus-250K-output workload, GPT-4.1 is cheaper by 11% ($4 vs $4.50). The gap changes for cache-heavy prompts and for batch jobs, as the workload table shows.
Which handles longer prompts, GPT-6.1 Sol or GPT-4.1?
GPT-6.1 Sol has the larger context window (1,050,000 vs 1,047,576 tokens). Watch the long-context threshold on GPT-6.1 Sol: rates rise once input passes it.
Do both models support prompt caching?
GPT-6.1 Sol bills cached reads at $0.10 per 1M; GPT-4.1 at $0.50.