// head_to_head
Muse Spark 1.2 vs GPT-5.6 Terra
Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.
Effectively the same quality — Muse Spark 1.2 is the cheaper way to get it.
The two are within 0.0 points overall, which is inside the range that effort settings alone move a LiveBench score, so treat them as quality-equivalent. Muse Spark 1.2 lists 2.3× cheaper per blended million tokens. When quality ties, cost is the whole decision.
meta
Muse Spark 1.2
- Blended / 1M
- $2.00
- Context
- 1.0M
- Released
- Aug 5, 2026
- Overall score
- 78.0
openai
GPT-5.6 Terra
- Blended / 1M
- $4.50
- Context
- 1.1M
- Released
- Jul 9, 2026
- Overall score
- 77.9
Specs and pricing
| Metric | Muse Spark 1.2 | GPT-5.6 Terra |
|---|---|---|
| LiveBench overall Mean of the seven LiveBench category scores, 0–100. Higher is better. | 78.0 | 77.9 |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.2199 | $0.1939 |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $2.00win | $4.50 |
| Input price / 1M | $1.25win | $2.00 |
| Output price / 1M | $4.25win | $12.00 |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | $0.150win | $0.200 |
| Context window | 1.0M | 1.1M |
| Max output tokens | — | 128K |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Muse Spark 1.2 on top, GPT-5.6 Terra below, both out of 100.
What each one costs to run
Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.
| Workload | Muse Spark 1.2 | GPT-5.6 Terra |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $560.80/mo | $1310.40/mo |
| RAG assistant 8K in / 600 out × 100K requests | $815.00/mo | $1600.00/mo |
| Coding agent 40K in / 4K out × 20K requests | $724.00/mo | $1552.00/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $1513.75/mo | $2810.00/mo |
| Bulk classification 500 in / 20 out × 5M requests | $3000.00/mo | $5300.00/mo |
Which should you pick?
The workload is coding or agentic work
Muse Spark 1.2
Leads on agentic coding — 57.6 against 54.9.
Muse Spark 1.2 vs GPT-5.6 Terra FAQ
Which is better, Muse Spark 1.2 or GPT-5.6 Terra?
Effectively the same quality — Muse Spark 1.2 is the cheaper way to get it. The two are within 0.0 points overall, which is inside the range that effort settings alone move a LiveBench score, so treat them as quality-equivalent. Muse Spark 1.2 lists 2.3× cheaper per blended million tokens. When quality ties, cost is the whole decision.
Is Muse Spark 1.2 cheaper than GPT-5.6 Terra?
Muse Spark 1.2 is cheaper. On a 3:1 input:output blend, Muse Spark 1.2 lists at $2.00 per million tokens and GPT-5.6 Terra at $4.50 — Muse Spark 1.2 is 2.3× cheaper. Input and output are priced separately — Muse Spark 1.2 charges $1.25 in and $4.25 out, GPT-5.6 Terra charges $2.00 and $12.00 — so the model that looks cheaper flips depending on how output-heavy your workload is.
Muse Spark 1.2 vs GPT-5.6 Terra: which scores higher on benchmarks?
Muse Spark 1.2 scores 78.0 and GPT-5.6 Terra scores 77.9 overall on LiveBench, the mean of its seven categories. That gap is inside the range that effort settings alone move a score, so treat them as equivalent on published quality. Category scores differ from the overall figure — a model can lead on reasoning and trail on coding, which the per-category table above breaks out.
Which gives better value for money, Muse Spark 1.2 or GPT-5.6 Terra?
They are close. Muse Spark 1.2 costs $0.2199 per point of overall capability and GPT-5.6 Terra costs $0.1939, a difference small enough that workload shape will matter more than the rate.
Does Muse Spark 1.2 or GPT-5.6 Terra have a bigger context window?
They are effectively the same — 1.0M for Muse Spark 1.2 and 1.1M for GPT-5.6 Terra.
Do Muse Spark 1.2 and GPT-5.6 Terra support prompt caching?
Both publish a cached-input rate: $0.150 per million for Muse Spark 1.2 and $0.200 for GPT-5.6 Terra, against full input rates of $1.25 and $2.00. On a workload with a long stable prefix — a system prompt, a tool schema, a retrieved corpus — that changes the economics more than the headline price does.
Related comparisons
How these numbers are produced
- Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
- Scores — LiveBench release 2026-06-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
- Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
- “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.
Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.