Gemini 2.5 Pro vs Muse Spark 1.2
Pricing verdict: Gemini 2.5 Pro vs Muse Spark 1.2: input pricing is tied at $1.25/M, Muse Spark 1.2 is cheaper for output-heavy usage ($4.25/M output), and Gemini 2.5 Pro is better for long-context tasks (2,000,000 tokens).
Direct answer: input pricing is tied. Choose Muse Spark 1.2 for cheaper output and choose Gemini 2.5 Pro when your workload needs longer context.
Compare API pricing, input and output token costs, context windows, and monthly estimates on one page so you can pick the right model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Gemini 2.5 Pro
Muse Spark 1.2
Cost Differences
Muse Spark 1.2 costs less than Gemini 2.5 Pro
Quick Recommendation
Winner for direct API pricing: Muse Spark 1.2. At the default workload, Muse Spark 1.2 saves about $8.625/month ($104.9375/year) versus Gemini 2.5 Pro.
Feature Comparison
| Feature | Gemini 2.5 Pro | Muse Spark 1.2 |
|---|---|---|
| Provider | Meta (via Together AI) | |
| Input Price | $1.25/1M tokens | $1.25/1M tokens |
| Output Price | $10.00/1M tokens | $4.25/1M tokens |
| Context Window | 2,000,000 tokens | 1,000,000 tokens |
| Max Output | 131,072 tokens | 131,072 tokens |
| Category | flagship | coding |
| Capabilities | textvisionaudiovideocode | textvisionaudiovideocodereasoning |
| Release Date | 3/25/2025 | 8/5/2026 |
Gemini 2.5 Pro vs Muse Spark 1.2: Which Should You Choose?
Choosing between Gemini 2.5 Pro and Muse Spark 1.2 depends on your priorities: cost efficiency, context length, or raw capability. Both models charge $1.25/1M input tokens, but Muse Spark 1.2 is cheaper on output at $4.25/1M. Meanwhile, Gemini 2.5 Pro offers a significantly larger context window at 2,000,000 tokens vs 1,000,000 for Muse Spark 1.2.
These models come from different providers — Google and Meta (via Together AI) — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Google, switching to Meta (via Together AI)involves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Gemini 2.5 Pro is a flagship model while Muse Spark 1.2 is coding. This means they're optimized for different workloads. Gemini 2.5 Pro is built for complex tasks that require deeper reasoning, while Muse Spark 1.2 offers better value for routine operations.
Output costs matter too. Gemini 2.5 Pro charges $10.00/1M output tokens vs $4.25 for Muse Spark 1.2. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Muse Spark 1.2 has the edge here at $4.25/1M output tokens.
Multimodal capabilities: Both models support vision (image understanding), so you can send images alongside text prompts with either option.
Best Use Cases
Choose Gemini 2.5 Pro when:
- • You need a larger context window (2,000,000 tokens)
- • You're already using Google's API ecosystem
Choose Muse Spark 1.2 when:
- • You need more capabilities (reasoning)
- • You're already using Meta (via Together AI)'s API ecosystem
Pros and Caveats at a Glance
Gemini 2.5 Pro
- • Input pricing: $1.25/M tokens
- • Output pricing: $10.00/M tokens
- • Context window: 2,000,000 tokens
- • Max output: 131,072 tokens
Watch out for
- • Higher output cost than Muse Spark 1.2
Muse Spark 1.2
- • Input pricing: $1.25/M tokens
- • Output pricing: $4.25/M tokens
- • Context window: 1,000,000 tokens
- • Max output: 131,072 tokens
Watch out for
- • Smaller context window than Gemini 2.5 Pro
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Gemini 2.5 Pro (Google)
Muse Spark 1.2 (Meta (via Together AI))
Start using Gemini 2.5 Pro today
Sign Up for Google →Start using Muse Spark 1.2 today
Sign Up for Meta (via Together AI) →Frequently Asked Questions
Which is cheaper, Gemini 2.5 Pro or Muse Spark 1.2?▼
What is the context window difference between Gemini 2.5 Pro and Muse Spark 1.2?▼
Which model is better for AI Chatbot?▼
Which model has better overall pricing for heavy usage?▼
Where can I compare Google and Meta (via Together AI) API pricing beyond this model matchup?▼
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