As of August 20, 2026, Grok-3 Mini is 57% cheaper per million tokens than Muse Glimmer-30B. Grok-3 Mini is $0.30 / $0.50 per million input/output tokens versus Muse Glimmer-30B at $0.35 / $1.50. Sources: https://docs.x.ai/docs/models and https://llama.meta.com/
Sources: xAI API pricing (https://docs.x.ai/docs/models); Meta pricing (https://llama.meta.com/)
Grok-3 Mini
xAI
Input
$0.30
Output
$0.50
Muse Glimmer-30B
Meta
Input
$0.35
Output
$1.50
Token pricing, specs, and benchmarks side by side
Grok-3 MiniMuse Glimmer-30BVerdict
Grok-3 Mini offers both lower pricing and stronger benchmark performance across the board, making it the clear value leader in this comparison.
As of August 20, 2026, Grok-3 Mini is 57% cheaper on blended LLM API pricing. Grok-3 Mini costs $0.30 per million input tokens and $0.50 per million output tokens ($0.80 blended 1M-in + 1M-out). Muse Glimmer-30B costs $0.35 / $1.50 per million tokens ($1.85 blended). Sources: https://docs.x.ai/docs/models and https://llama.meta.com/. The cheapest LLM for your app still depends on how many output tokens you generate.
Grok-3 Mini xAI API pricing is $0.30 input and $0.50 output per million tokens via xAI. Muse Glimmer-30B Meta API pricing is $0.35 input and $1.50 output per million tokens via Meta. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Muse Glimmer-30B has a published SWE-bench Verified score of 76%. Grok-3 Mini does not have that eval on this page yet.
Grok-3 Mini supports a 128K token context window, while Muse Glimmer-30B supports 131K tokens. Muse Glimmer-30B 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.
Grok-3 Mini leads on 1 of 1 shared benchmarks versus Muse Glimmer-30B'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.
Both Grok-3 Mini and Muse Glimmer-30B are production API models. For cost-sensitive production traffic, Grok-3 Mini 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.
Yes. Call Grok-3 Mini through xAI and Muse Glimmer-30B 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.
List rates are the latest published xAI API pricing and Meta API pricing, quoted per million tokens. Official rate sheets: https://docs.x.ai/docs/models 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.
Grok-3 Mini supports up to 8K output tokens per request, while Muse Glimmer-30B supports up to an unspecified number of output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Grok-3 Mini has a measured throughput of approximately 100 tokens/second. Throughput data for Muse Glimmer-30B is not yet available. 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.
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Grok-3 Mini or Muse Glimmer-30B from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
This comparison covers API pricing, context window, throughput, and benchmark scores. Grok-3 Mini costs $0.30/M input and $0.50/M output. Muse Glimmer-30B costs $0.35/M input and $1.50/M output.
Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.
The index
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