Muse Spark is Meta's best model for research — it scores 90/100 vs 78/100 for Llama 4 Scout, at $1.25/1M input tokens. Across all providers, GPT-6 Astra still leads research at 100/100 — worth considering if you're not committed to Meta.
The safest meta model for research default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Muse Spark is the strongest answer here for meta model for research — pick it when quality of output matters more than the $1.25/1M/1M input you pay for it.
Muse Glimmer 30B handles the same job for about 66% less per token. Start here and only move up if the output is not good enough.
Llama 4 Scout carries 512k tokens of context, so it is the pick for meta model for research when whole documents, transcripts, or repositories go in at once.
Muse Spark leads Meta's lineup for research at 90/100 ($1.25/1M input, 1.048576M context).
Muse Glimmer 30B is the value pick at $0.35/1M input with a research score of 76/100.
GPT-6 Astra (OpenAI) is the overall research leader at 100/100 if provider choice is open.
Choose Muse Spark when research quality is the priority and you're staying on Meta.
Choose Muse Glimmer 30B when token volume matters more than peak quality.
Teams open to other providers should also evaluate GPT-6 Astra before committing.
Switch the scoring lens to see whether the meta model for research answer changes when cost, speed, or long-document depth leads the decision.
Meta / Balanced / Aug 6, 2026
Best-value multimodal agentic model — GPT-5.5-tier smarts, video/audio/PDF in.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need frontier-ceiling reasoning or a mature developer ecosystem — Opus 5 and GPT-5.6 lead both.
Where the meta model for research recommendation shifts once you weigh price or latency differently.
Best-value multimodal agentic model — GPT-5.5-tier smarts, video/audio/PDF in.
Best open-weight long-context option for self-hosted pipelines.
Apache 2.0 agent model that runs on a 24GB GPU.
Best flexible option for teams that need open-weight portability.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Muse SparkMeta | $1.25/1M | $4.25/1M | $21 | 1.0M tokens | Balanced | 89 | 88 | 90 |
| Llama 4 ScoutMeta | $0.50/1M | $1.20/1M | $7.40 | 512k tokens | Fast | 54 | 60 | 78 |
| Muse Glimmer 30BMeta | $0.35/1M | $1.50/1M | $6.50 | 131k tokens | Fast | 80 | 74 | 76 |
| Llama 4 MaverickMeta | $0.60/1M | $1.60/1M | $9.20 | 256k tokens | Fast | 58 | 66 | 64 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for meta model for research, what it is genuinely good at, and where we would steer you away from it.
Our pick for meta model for research. It scores 72/100 on the budget axis we weight this page by, and nothing else in this shortlist matches it on output quality.
Meta Superintelligence Labs' first closed frontier model — a natively multimodal agentic reasoner (text, image, video, audio, PDF in) with a parallel-agent 'Contemplating mode', priced aggressively below rivals.
You need frontier-ceiling reasoning or a mature developer ecosystem — Opus 5 and GPT-5.6 lead both.
Meta's surprise pivot to closed frontier models is a genuine value play: GPT-5.5-tier intelligence with the broadest multimodal input support, at prices that undercut OpenAI and Anthropic. The young API ecosystem is the main practical drawback.
Full pricing, benchmark table and release notes on the Muse Spark page.
In this line-up because of context depth: the pick for meta model for research when the input is too big to chunk.
Long-window open-weight model that handles large document sets at a low price point.
You want a hosted solution — Gemini 3.1 Flash gives more context for roughly the same cost.
A compelling pick for self-hosted long-context pipelines — but Gemini 3.1 Flash now offers 1M context hosted at a similar price.
Full pricing, benchmark table and release notes on the Llama 4 Scout page.
The cost-conscious pick for meta model for research, about 66% less per token than Muse Spark than the top choice while holding 90/100 on budget.
Apache 2.0 agent model that runs on a 24GB GPU. Full Muse Glimmer 30B review →
The alternative to check next for meta model for research — 78/100 on budget.
Best flexible option for teams that need open-weight portability. Full Llama 4 Maverick review →
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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Muse Spark — it scores 90/100 on research in this directory, ahead of Llama 4 Scout at 78/100. Best-value multimodal agentic model — GPT-5.5-tier smarts, video/audio/PDF in.
Not overall. GPT-6 Astra (OpenAI) leads the directory for research at 100/100 vs Muse Spark's 90/100. Muse Spark is the best pick if you're staying within Meta's ecosystem.
Muse Glimmer 30B at $0.35/1M input tokens (research score: 76/100). Use it for volume work and reserve Muse Spark for the tasks where quality matters most.
$1.25/1M input tokens and $4.25/1M output tokens via the API, or through Meta AI (free) at $0/mo for chat use. Context window: 1.048576M tokens. On a moderate month — 10M input and 2M output tokens — that works out to about $21.00, against $6.50 for Muse Glimmer 30B.
Trails the frontier on raw intelligence: AA Intelligence Index 54 vs Claude Opus 5 (61) and GPT-5.6 Sol (59). Weak on some hard agentic evals (27% tau3-Banking) and the API ecosystem is young — public API only since July 2026. Concretely, avoid it if you need frontier-ceiling reasoning or a mature developer ecosystem — Opus 5 and GPT-5.6 lead both. If none of that is negotiable, GPT-6 Astra (OpenAI) is the cross-provider leader at 100/100.
agentic productivity work — powers Meta AI's email/calendar/slides agents since v1.1, terminal coding via the new Muse Code agent (v1.2 is coding-focused, 80% Terminal-Bench 2.1), and health and science reasoning — Contemplating mode hit 58% on Humanity's Last Exam. Its 1.048576M-token context window is the practical limit on how much you can hand it in one go.
Muse Spark scores 90/100 on research against 76/100 for Muse Glimmer 30B, at 4x the input price. That premium is worth it on work where a wrong answer costs real time or money, and hard to justify on high-volume, low-stakes calls. Most teams run both and route by task rather than picking one.