AI model comparison
Muse Spark 1.3 Contributor vs Llama 3.3 70B Instruct
Side by side comparison of Muse Spark 1.3 Contributor and Llama 3.3 70B Instruct on pricing, benchmark scores, context window, and more.
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows.
- Input / 1M
- $0.10
- Output / 1M
- $0.20
- Context
- 1.05M
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out).
- Input / 1M
- $0.10
- Output / 1M
- $0.32
- Context
- 131K
Comparing image generators? Compare image models
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Muse Spark 1.3 Contributor
1.2x cheaper for a typical chat
Higher intelligence score
Not available
Not enough benchmark data
Larger context window
Muse Spark 1.3 Contributor
1.05M vs 131K tokens
Newer release
Muse Spark 1.3 Contributor
Released September 2, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
Muse Spark 1.3 Contributor vs Llama 3.3 70B Instruct API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.10 | $0.10 |
| Output tokensPer 1M tokens | $0.20 | $0.32 |
| Cached input (read)Per 1M tokens | $0.00 | Not available |
| Cache writePer 1M tokens | Not available | Not available |
| Web searchPer request | $0.0025 | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 1.05M tokens | 131K tokens |
| Max output | 944K tokens | 16K tokens |
| Input types | File, Image, Text, Video | Text |
| Output types | Text | Text |
| Reasoning effort levels | Max, Extra high, High, Medium, Low, Minimal | Not available |
| Default reasoning effort | Medium | Not available |
| Release date | September 2, 2026 | December 6, 2024 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Not supported |
| Temperature | Supported | Supported |
| Stop sequences | Not supported | Supported |
| Deterministic seed | Not supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
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Our take
Muse Spark 1.3 Contributor is 1.2x cheaper for a typical chat. Muse Spark 1.3 Contributor has the larger context window (1.05M vs 131K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is Muse Spark 1.3 Contributor or Llama 3.3 70B Instruct cheaper?
Muse Spark 1.3 Contributor is cheaper for a typical chat (2K input tokens and 500 output tokens). Muse Spark 1.3 Contributor costs $0.10 per 1M input tokens and $0.20 per 1M output tokens, while Llama 3.3 70B Instruct costs $0.10 per 1M input tokens and $0.32 per 1M output tokens.
Which has a bigger context window, Muse Spark 1.3 Contributor or Llama 3.3 70B Instruct?
Muse Spark 1.3 Contributor supports up to 1.05M tokens of context, compared with 131K for Llama 3.3 70B Instruct.
Can I use Muse Spark 1.3 Contributor and Llama 3.3 70B Instruct at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Muse Spark 1.3 Contributor and Llama 3.3 70B Instruct answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Muse Spark 1.3 Contributor and Llama 3.3 70B Instruct at the same time. Compare the answers side by side and keep the best one.