GPT-5.6 Terra vs Muse Spark Open
Muse Spark Open and GPT-5.6 Terra score 69.4% vs 66.0% averaged across five Vision Evals tasks (#25 and #28 of 65 models), so Muse Spark Open leads overall.
- Muse Spark Open wins 3 of the 5 tasks, with its widest lead on OCR (67.6% vs 56.3%).
- Muse Spark Open is about half the cost: $0.0059 vs $0.010 overall average cost per sample.
- Muse Spark Open is faster: 7.4s vs 9.5s per sample.
Roboflow Vision Evals. Full breakdown below.
Compare GPT-5.6 Terra vs Muse Spark Open live
Run the same image across every model that supports a task and compare their outputs side-by-side.
These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
GPT-5.6 Terra vs Muse Spark Open on Vision Evals
Roboflow Vision Evals. Full breakdown below.
GPT-5.6 Terra vs Muse Spark Open Comparison Table
Evals updated October 26, 2026Pricing updated October 27, 2026
| Property | GPT-5.6 Terra | Muse Spark Open |
|---|---|---|
| Organization | OpenAI | Meta |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Jul 2026 | Oct 2026 |
| Context Window | 1.1M | 1.0M |
| Parameters | Unknown | 816B total / 42B active |
| License | Proprietary | Custom |
| Commercial use | commercial use per vendor terms | See license terms |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $1.25 |
| Output $/1M | $12.00 | $4.25 |
| Vision Tasks | ||
| Captioning | Demo | Supported |
| Classification | Demo | Supported |
| Object Detection | Demo | Supported |
| OCR | Demo | Supported |
| Visual Question Answering | Demo | Supported |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 66.0% | 69.4% |
| Avg cost / sample | $0.010 | $0.0059 |
| Avg speed / sample | 9.52s | 7.37s |
| By task | ||
| Object Detection (low) | 60.6% ±0.2, Mean of 3 runs, range 60.3 to 60.7 | 57.8% ±0.6, Mean of 3 runs, range 57.0 to 58.2 |
| Object Detection (high) | 61.3% ±0.4, Mean of 3 runs, range 60.8 to 61.6 | 60.9% ±0.8, Mean of 3 runs, range 60.3 to 61.9 |
| Counting (low) | 65.8% ±2.0, Mean of 3 runs, range 63.5 to 67.6 | 75.7% ±2.7, Mean of 3 runs, range 73.0 to 78.4 |
| Counting (high) | 62.6% ±2.7, Mean of 3 runs, range 59.5 to 64.9 | 75.2% ±4.1, Mean of 3 runs, range 71.6 to 79.7 |
| Identification (low) | 86.5% ±1.6, Mean of 3 runs, range 84.4 to 87.5 | 82.3% ±1.6, Mean of 3 runs, range 81.3 to 84.4 |
| Identification (high) | 86.5% ±3.1, Mean of 3 runs, range 84.4 to 90.6 | 80.2% ±3.1, Mean of 3 runs, range 78.1 to 84.4 |
| OCR (low) | 56.3% | 67.6% |
| by category |
|
|
| OCR (high) | 56.9% | 68.6% |
| by category |
|
|
| Reasoning (low) | 60.9% ±2.0, Mean of 3 runs, range 59.6 to 63.6 | 63.8% ±1.0, Mean of 3 runs, range 62.9 to 64.9 |
| Reasoning (high) | 65.3% ±1.0, Mean of 3 runs, range 64.2 to 66.2 | 65.1% ±3.0, Mean of 3 runs, range 62.3 to 68.2 |
GPT-5.6 Terra vs Muse Spark Open: Overview
GPT-5.6 Terra is the mid-tier reasoning model in OpenAI's GPT-5.6 family, which also includes the flagship Sol and the lightweight Luna. Introduced in a limited preview on June 26, 2026, and made broadly available on July 9, 2026, Terra accepts text and image input and produces text output, supporting vision, function calling, tool use, and agentic workflows. It is designed as a balanced option for everyday professional and production workloads — including coding assistance, document analysis, customer support, and multi-step agent tasks — where both output quality and cost efficiency matter. OpenAI positions Terra as delivering performance competitive with GPT-5.5 at approximately half the price, with a context window of around 1,050,000 tokens. Under OpenAI's Preparedness Framework, Terra is rated High for cybersecurity and biological capabilities, meaning it demonstrates meaningful capability in those domains without reaching the Critical threshold.
GPT-5.6 introduces a new naming convention in which the generation number (5.6) is paired with a durable capability tier name (Sol, Terra, or Luna), allowing each tier to advance on its own schedule. Terra carries the API identifier gpt-5.6-terra and supports the same reasoning effort controls available across the family, including adjustable reasoning depth. The model includes prompt caching with explicit cache breakpoints and a 30-minute minimum cache life, with cache writes billed at 1.25x the uncached input rate and cache reads receiving a 90% discount. GPT-5.6 Terra is a proprietary, closed-weights model served through the OpenAI API, Codex, and ChatGPT.
Muse Spark Open is an open-weight multimodal model released by Meta on October 15, 2026. Its sparse mixture-of-experts architecture has 816 billion total parameters and activates 42 billion per token. It accepts text, images, audio and video, produces text, and supports a context window of 1,048,576 tokens. Meta provides BF16 and NVFP4 checkpoints for self-hosting, alongside access through hosted inference partners.
The model is designed for coding, tool use and multi-step reasoning over long tasks. Its visual inputs support workflows involving screenshots, documents and other image content. Vision Evals measures its text understanding, counting, identification, reasoning and object detection at Low and High effort. The published weights use the custom Muse Model License, with commercial use subject to its terms and the accompanying usage policy.
Frequently Asked Questions
On Roboflow's Vision Evals, Muse Spark Open performed better. It scores higher on 3 of the five vision tasks and averages 69.4% (#25 of 65) against 66.0% (#28 of 65) for GPT-5.6 Terra. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals OCR benchmark at low effort, Muse Spark Open leads with 67.6% against 56.3%. This is the widest gap between the two models across the benchmark's tasks.
Muse Spark Open is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0059 per sample against $0.010. GPT-5.6 Terra is priced at $2.00 per 1M input tokens and $12.00 per 1M output; Muse Spark Open is priced at $1.25 per 1M input tokens and $4.25 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Muse Spark Open is faster. Across Roboflow's Vision Evals it averaged 7.4s per inference against 9.5s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.