Data verified: Oct 27, 2026, 9:28 AM UTC · Prices sourced from official provider pages. Verify current rates before production use.

MiniMax M2-her vs Muse Spark 1.3 Contributor

Price, context and performance head to head. Data synced from the provider catalog.

Quick verdict

Cheaper

Muse Spark 1.3 Contributor

Larger context

Muse Spark 1.3 Contributor

Faster

MiniMax M2-her

Higher quality

Muse Spark 1.3 Contributor

Head-to-head

Head-to-head
Feature	MiniMax M2-her	Muse Spark 1.3 Contributor
Provider	MiniMax	Meta
Tier	Budget	Mid-tier
Input per 1M tokens	$0.3	$0.1
Output per 1M tokens	$1.2	$0.2
Cached input per 1M	$0.03	$0.002
Context window	65.5K	1.0M
Intelligence index	—	—
Coding index	—	—
Agentic index	—	—
GPQA Diamond	—	—
Tau-bench (airline)	—	—
Speed	Fast	Standard
Vision (image input)	No	Yes
Function calling	No	Yes
Batch API	No	No

Estimated monthly cost

Enter how many requests per day you send with an average prompt (1K input + 1K output) and compare the monthly cost of both models.

Requests per day

MiniMax M2-her

$4.5

/ mo

Muse Spark 1.3 Contributor

$0.9

/ mo

Muse Spark 1.3 Contributor saves $3.6/mo vs MiniMax M2-her

Which one should I pick?

Pick Muse Spark 1.3 Contributor if cost is the priority: it's 80% cheaper than MiniMax M2-her on an average prompt.
Pick Muse Spark 1.3 Contributor if you need to process long documents: its context window is 16× larger.
Pick Muse Spark 1.3 Contributor if answer quality is the priority: it's better positioned for your use case.
Pick MiniMax M2-her if latency matters: it's noticeably faster.

Want us to build it for you?

We integrate MiniMax M2-her or Muse Spark 1.3 Contributor into your product with caching, observability and continuous evaluation — typically 40-80% cheaper than the obvious first pick.

Talk to an expert

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Frequently asked questions about AI models and pricing

What people ask us when comparing GPT, Claude, Gemini and the rest.

A token is the unit an AI model processes: usually between half a word and a full word. Rule of thumb: 1,000 tokens ≈ 750 English words. A 20-word sentence is about 26 tokens; a 300-word email is around 400. Models charge for input tokens (your prompt) and output tokens (their answer) separately.

When your app sends the same system prompt on every request (e.g. "You are a customer support agent for Acme…"), providers store it once and reuse the computation. They only charge full price for the new part (the user's question). OpenAI, Anthropic and Google give 50% to 90% off cached tokens. The calculator above accounts for this via a cache-hit % slider.

Chatbot: GPT-5.4 Mini or Claude Haiku 4.5 for latency; DeepSeek V3.2 for cost. Code: Claude Opus 4.6 and GPT-5.4 still lead the benchmarks, with o3 and DeepSeek R1 for hard reasoning. Document analysis: you need a large window — Gemini 3.1 Pro, Claude Opus or Llama 4 Maverick. Use the Model Finder above for a personalised pick.

Five levers: (1) cache system prompts (saves 50-90%), (2) batch API for non-urgent requests (50% off), (3) smaller model for simple tasks and flagship only when needed (complexity router), (4) trim prompts and cap output tokens, (5) fine-tune or use RAG instead of re-sending the same context every call. At Letbrand we audit each lever and typically cut costs by 40-80%.

MiniMax M2-her vs Muse Spark 1.3 Contributor

Price, context and performance head to head. Data synced from the provider catalog.

Quick verdict

Cheaper

Muse Spark 1.3 Contributor

Larger context

Muse Spark 1.3 Contributor

Faster

MiniMax M2-her

Higher quality

Muse Spark 1.3 Contributor

Head-to-head

Head-to-head
Feature	MiniMax M2-her	Muse Spark 1.3 Contributor
Provider	MiniMax	Meta
Tier	Budget	Mid-tier
Input per 1M tokens	$0.3	$0.1
Output per 1M tokens	$1.2	$0.2
Cached input per 1M	$0.03	$0.002
Context window	65.5K	1.0M
Intelligence index	—	—
Coding index	—	—
Agentic index	—	—
GPQA Diamond	—	—
Tau-bench (airline)	—	—
Speed	Fast	Standard
Vision (image input)	No	Yes
Function calling	No	Yes
Batch API	No	No

Estimated monthly cost

Enter how many requests per day you send with an average prompt (1K input + 1K output) and compare the monthly cost of both models.

Requests per day

MiniMax M2-her

$4.5

/ mo

Muse Spark 1.3 Contributor

$0.9

/ mo

Muse Spark 1.3 Contributor saves $3.6/mo vs MiniMax M2-her

Which one should I pick?

Pick Muse Spark 1.3 Contributor if cost is the priority: it's 80% cheaper than MiniMax M2-her on an average prompt.
Pick Muse Spark 1.3 Contributor if you need to process long documents: its context window is 16× larger.
Pick Muse Spark 1.3 Contributor if answer quality is the priority: it's better positioned for your use case.
Pick MiniMax M2-her if latency matters: it's noticeably faster.

Want us to build it for you?

We integrate MiniMax M2-her or Muse Spark 1.3 Contributor into your product with caching, observability and continuous evaluation — typically 40-80% cheaper than the obvious first pick.

Talk to an expert