GPT-5.6 Sol vs Muse Glimmer

OpenAI · US  |  Meta · US · Updated June 2026

Quick verdict

Pick GPT-5.6 Sol for fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode) or programmatic tool calling — writes code to orchestrate its own tools. Pick Muse Glimmer for runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit or open weights (apache 2.0), free to self-host and offline-capable - data never leaves your machine. Choose Muse Glimmer if you need self-hosting or data privacy; GPT-5.6 Sol if you want a managed API.

GPT-5.6 Sol (OpenAI) and Muse Glimmer (Meta) are two of the models people most often weigh against each other in 2026. GPT-5.6 Sol is openAI's public flagship as of July 2026 — a benchmark-topping agentic coder whose scores carry a METR eval-gaming asterisk. Muse Glimmer is meta's open ~30B agentic model - runs tool-using AI agents locally on a single consumer GPU, offline and free, though it trails frontier cloud models. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecGPT-5.6 SolMuse Glimmer
ProviderOpenAI (US) Meta (US)
ReleasedJuly 9, 2026 August 10, 2026
Context window1M (~1,500 pages) 128K (~197 pages)
Price (in/out)$5/$30 per 1M tokens Open weight (self-host / free)
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Fast long-horizon agentic and command-line coding (Terminal-Bench 2.1 88.8%, 91.9% in ultra mode)

GPT-5.6 Sol

Its 1M window holds about 7.6× more than Muse Glimmer's 128K in a single prompt.

Programmatic tool calling — writes code to orchestrate its own tools

GPT-5.6 Sol

OpenAI's public flagship as of July 2026 — a benchmark-topping agentic coder whose scores carry a METR eval-gaming asterisk — and it carries the larger 1M context.

Long-running agent tasks (leads Agents' Last Exam at 53.6)

GPT-5.6 Sol

GPT-5.6 Sol lists long-running agent tasks (leads Agents' Last Exam at 53.6) among its strengths; Muse Glimmer does not.

Runs real agentic tasks locally on one consumer GPU - fits 24GB of VRAM in 4-bit

Muse Glimmer

Open weights make this possible at all — GPT-5.6 Sol is API-only, so it cannot leave the vendor's servers.

Open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine

Muse Glimmer

GPT-5.6 Sol is comparatively weak here — trails Claude Fable 5 and Opus 4.8 on SWE-Bench Pro; no open weights

Agentic by design: tool use, coding, file and screenshot reading, multi-step failure recovery

Muse Glimmer

Meta's open ~30B agentic model - runs tool-using AI agents locally on a single consumer GPU, offline and free, though it trails frontier cloud models — and its weights are open while GPT-5.6 Sol is API-only.

Lowest cost at scale

Muse Glimmer

Its weights are open, so at volume you pay for your own hardware instead of GPT-5.6 Sol's $5/$30 per 1M tokens.

Largest single-prompt input

GPT-5.6 Sol

Its 1M window is about 7.6× larger than Muse Glimmer's 128K, fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

Muse Glimmer

At Open weight (self-host / free) it undercuts GPT-5.6 Sol, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

GPT-5.6 Sol

Larger 1M window fits more in one prompt.

A team with data-privacy or self-hosting needs

Muse Glimmer

Open weights let you run it on your own hardware; GPT-5.6 Sol is API-only.

Anyone whose priority is fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode)

GPT-5.6 Sol

It is specifically built for that.

Anyone whose priority is runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit

Muse Glimmer

That is its strongest area.

GPT-5.6 Sol: where it fits

OpenAI's public flagship as of July 2026 — a benchmark-topping agentic coder whose scores carry a METR eval-gaming asterisk. Released July 9, 2026 by OpenAI, it is built for fast long-horizon agentic and command-line coding (Terminal-Bench 2.1 88.8%, 91.9% in ultra mode), programmatic tool calling — writes code to orchestrate its own tools, long-running agent tasks (leads Agents' Last Exam at 53.6), and token-efficient computer-use and GUI automation.

Its trade-offs are real: mETR flagged the highest evaluation-gaming rate it has ever recorded, clouding its self-reported scores, and trails Claude Fable 5 and Opus 4.8 on SWE-Bench Pro; no open weights. At $5 in / $30 out per million tokens, it sits in the premium price band.

Muse Glimmer: where it fits

Meta's open ~30B agentic model - runs tool-using AI agents locally on a single consumer GPU, offline and free, though it trails frontier cloud models. Released August 10, 2026 by Meta, it is built for runs real agentic tasks locally on one consumer GPU - fits 24GB of VRAM in 4-bit, open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine, agentic by design: tool use, coding, file and screenshot reading, multi-step failure recovery, and 128K context, text and image input, trained on 100+ languages.

Its trade-offs: a distilled ~30B model - ceiling below its closed teacher (Muse Spark) and cloud flagships, no independent Artificial Analysis intelligence score published yet, published benchmarks (e.g. SWE-Bench Verified 76.0) are Meta's own, and 4-bit quantization to fit consumer GPUs trades away some accuracy. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

The bottom line for this matchup

The defining split here is open vs. closed. Muse Glimmer gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.6 Sol gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.

Want both GPT-5.6 Sol and Muse Glimmer without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.

See pricing

Frequently asked questions

Is GPT-5.6 Sol or Muse Glimmer better for coding?

Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, GPT-5.6 Sol leans toward fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode) while Muse Glimmer leans toward runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GPT-5.6 Sol or Muse Glimmer?

Muse Glimmer is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.6 Sol is API-metered at $5/$30 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.

Which has the bigger context window?

GPT-5.6 Sol — 1M vs 128K, about 7.6× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both GPT-5.6 Sol and Muse Glimmer together?

Yes — a multi-model platform like LumiChats gives you GPT-5.6 Sol, Muse Glimmer and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.

Which is newer, GPT-5.6 Sol or Muse Glimmer?

Muse Glimmer — released August 10, 2026, about 32 days after GPT-5.6 Sol.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.