Muse Spark is Meta's best model for coding — it scores 89/100 vs 80/100 for Muse Glimmer 30B, at $1.25/1M input tokens. Across all providers, GPT-6 Astra still leads coding at 100/100 — worth considering if you're not committed to Meta.
The safest meta model for coding 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 coding — 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 Maverick is the fastest of these for meta model for coding — worth it when latency is what the reader notices, not the last few points of reasoning depth.
Muse Spark leads Meta's lineup for coding at 89/100 ($1.25/1M input, 1.048576M context).
Muse Glimmer 30B is the value pick at $0.35/1M input with a coding score of 80/100.
GPT-6 Astra (OpenAI) is the overall coding leader at 100/100 if provider choice is open.
Choose Muse Spark when coding 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 coding 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 coding recommendation shifts once you weigh price or latency differently.
Best-value multimodal agentic model — GPT-5.5-tier smarts, video/audio/PDF in.
Apache 2.0 agent model that runs on a 24GB GPU.
Best flexible option for teams that need open-weight portability.
Best open-weight long-context option for self-hosted pipelines.
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 |
| 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 |
| Llama 4 ScoutMeta | $0.50/1M | $1.20/1M | $7.40 | 512k tokens | Fast | 54 | 60 | 78 |
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 coding, what it is genuinely good at, and where we would steer you away from it.
The default answer for meta model for coding — 72/100 on the budget axis, and the model we would start with unless the price below rules it out.
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.
The value option for meta model for coding: about 66% less per token than Muse Spark, at 90/100 on budget. Worth starting here and moving up only if the output disappoints.
Meta's return to genuine open source — a 30B dense model under Apache 2.0, built for always-on agents rather than chat, and the first release from Meta Superintelligence Labs.
You need a large context window or the strongest agent scores at this size — check Qwen's 27B first.
The best Apache 2.0 agent model you can run on consumer hardware right now. Pick it when licence freedom and local execution matter more than the last few benchmark points — otherwise Qwen3.6-27B edges it on agent tasks.
Full pricing, benchmark table and release notes on the Muse Glimmer 30B page.
The fastest model in this shortlist for meta model for coding. Pick it when turnaround is what your readers or users notice.
Best flexible option for teams that need open-weight portability. Full Llama 4 Maverick review →
Rounds out the shortlist for meta model for coding at 86/100 on budget.
Best open-weight long-context option for self-hosted pipelines. Full Llama 4 Scout 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 89/100 on coding in this directory, ahead of Muse Glimmer 30B at 80/100. Best-value multimodal agentic model — GPT-5.5-tier smarts, video/audio/PDF in.
Not overall. GPT-6 Astra (OpenAI) leads the directory for coding at 100/100 vs Muse Spark's 89/100. Muse Spark is the best pick if you're staying within Meta's ecosystem.
Muse Glimmer 30B at $0.35/1M input tokens (coding score: 80/100). 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 89/100 on coding against 80/100 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.