Which is cheaper, Mistral Medium 3.5 or Muse Spark 1.1?
As of August 20, 2026, Muse Spark 1.1 is 39% cheaper on blended LLM API pricing. Muse Spark 1.1 costs $1.25 per million input tokens and $4.25 per million output tokens ($5.50 blended 1M-in + 1M-out). Mistral Medium 3.5 costs $1.50 / $7.50 per million tokens ($9.00 blended). Sources: https://docs.mistral.ai/platform/pricing/ and https://llama.meta.com/. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does Mistral Medium 3.5 vs Muse Spark 1.1 cost per million tokens?
Mistral Medium 3.5 Mistral API pricing is $1.50 input and $7.50 output per million tokens via Mistral AI. Muse Spark 1.1 Meta API pricing is $1.25 input and $4.25 output per million tokens via Meta. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, Mistral Medium 3.5 or Muse Spark 1.1?
Muse Spark 1.1 leads on SWE-bench Verified: Mistral Medium 3.5 at 77.6% vs Muse Spark 1.1 at 82%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
What is the context window for Mistral Medium 3.5 vs Muse Spark 1.1?
Mistral Medium 3.5 supports a 256K token context window, while Muse Spark 1.1 supports 1M tokens. Muse Spark 1.1 offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, Mistral Medium 3.5 or Muse Spark 1.1?
Muse Spark 1.1 leads on 16 of 16 shared benchmarks versus Mistral Medium 3.5's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is Mistral Medium 3.5 or Muse Spark 1.1 better for production use?
Both Mistral Medium 3.5 and Muse Spark 1.1 are production API models. For cost-sensitive production traffic, Muse Spark 1.1 has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between Mistral Medium 3.5 and Muse Spark 1.1 in my app?
Yes. Call Mistral Medium 3.5 through Mistral AI and Muse Spark 1.1 through Meta with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this Mistral Medium 3.5 vs Muse Spark 1.1 pricing data?
List rates are the latest published Mistral API pricing and Meta API pricing, quoted per million tokens. Official rate sheets: https://docs.mistral.ai/platform/pricing/ and https://llama.meta.com/. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for Mistral Medium 3.5 and Muse Spark 1.1?
Mistral Medium 3.5 supports up to 256K output tokens per request, while Muse Spark 1.1 supports up to 131K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, Mistral Medium 3.5 or Muse Spark 1.1?
Mistral Medium 3.5 runs at approximately 0.9605563235026328 tokens/second while Muse Spark 1.1 runs at 6.152425085592334 tokens/second. Muse Spark 1.1 is faster in raw throughput. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this Mistral Medium 3.5 vs Muse Spark 1.1 comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Mistral Medium 3.5 or Muse Spark 1.1 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.