Meta's Muse Spark 1.3 and OpenAI's GPT-6.1 Sol are both strong-tier models with 1M-token context windows, but they are priced on different curves. Muse Spark is cheaper on fresh input and much cheaper on output; Sol fights back only on cache hits.
Muse Spark 1.3 is the cheaper model for most workloads, mainly because its output rate is $4.25 against $10.00 per 1M tokens. GPT-6.1 Sol only pulls ahead on input that is almost entirely cache hits ($0.10 vs $0.15) with very little generated text.
| Muse Spark 1.3 | GPT-6.1 Sol | |
|---|---|---|
| Provider | Meta | OpenAI |
| Tier | Mid-tier | Mid-tier |
| Input / 1M tokens | $1.25 | $2.00 |
| Output / 1M tokens | $4.25 | $10.00 |
| Cache hit / 1M | $0.15 | $0.10 |
| Cache write / 1M | — | $2.50 |
| Context window | 1M | 1M |
| Notes | Meta's first paid model, agentic; 1.3 succeeds 1.2 at same price (Sep 2, 2026 efficiency update) | New (Sep 29, 2026 DevDay), below Astra in the GPT-6 family; replaces GPT-6 Sol at the same input/output price with a 50% cheaper cache-read rate; >272K tokens: $4/$15, cache $0.20. ChatGPT Work/Codex on Plus/Pro/Business/Enterprise/Edu, plus API |
Muse Spark 1.3 is 38% cheaper on input tokens ($1.25 vs $2.00 per 1M). Muse Spark 1.3 is 2.4× cheaper on output tokens ($4.25 vs $10.00 per 1M).
| Workload | Muse Spark 1.3 | GPT-6.1 Sol | Difference |
|---|---|---|---|
| Support chatbot 10,000 conversations × (2,000 input + 400 output tokens) | $42.00 | $80.00 | Muse Spark 1.3 saves $38.00 |
| Document Q&A 1,000 questions × (30,000 input + 800 output tokens) | $40.90 | $68.00 | Muse Spark 1.3 saves $27.10 |
| Coding agent session 4M input tokens (90% cache hits) + 150,000 output tokens | $1.68 | $2.66 | Muse Spark 1.3 saves $0.98 |
Standard rates per 1M tokens from data on this site. The coding-agent row assumes 90% of input is read from the prompt cache (full input price where a model has no cache rate). Cache-write fees, batch discounts and long-context surcharges listed in the notes are not included. Updated November 2, 2026.
your traffic is output-heavy or mostly uncached — chat, drafting, agent loops that write a lot — and you want one flat rate whether a prompt is 10K or 800K tokens.
you reuse a large, stable prompt prefix thousands of times with short answers, you can push non-urgent jobs through OpenAI's half-price Batch API, or you want the same model your team uses in ChatGPT Work and Codex.
Sol's cache hit costs $0.10 per 1M tokens versus $0.15 on Muse Spark, so on reused input Sol is the cheaper model. Sol also charges $2.50 per 1M to write the cache in the first place, and our table lists no separate write rate for Muse Spark. In practice output decides the bill: in the coding-agent example above, 90% cache hits still leave Muse Spark cheaper because Sol's $10.00 output rate swamps the savings. Sol only wins on jobs like classification or extraction against a big shared system prompt, where answers are a few tokens long.
GPT-6.1 Sol switches to a long-context rate once a prompt exceeds 272K tokens: $4/$15 per 1M, with cache hits at $0.20. No long-context tier is listed for Muse Spark 1.3, so if you send whole repositories or long contract bundles, compare Muse Spark against Sol's long-context rate rather than its headline price — the gap widens further.
OpenAI's Batch API halves Sol's input, cached-input and output rates for asynchronous jobs, which brings Sol's batch output price close to Muse Spark's standard rate — worth testing if your workload can wait. On the Meta side, Muse Spark 1.3 replaced 1.2 at the same price in a Sep 2, 2026 efficiency update, and GPT-6.1 Sol replaced GPT-6 Sol at the same input/output price with a cheaper cache read, so neither upgrade changed what existing users pay per token.
On standard rates, yes: $1.25 input and $4.25 output per 1M tokens versus $2.00 and $10.00. Sol is cheaper only on cache hits.
Both list 1M tokens. The difference is price at the top end: Sol bills prompts over 272K tokens at a higher long-context rate, while no such tier is listed for Muse Spark.
Yes. OpenAI's pricing page lists Batch API rates at half the standard input, cached-input and output prices for Sol, including its long-context tier.
How we choose: prices come from each vendor's official pricing page and are re-checked every week. We take no affiliate fees, so rankings aren't for sale.