MAI-Code-1.1-Flash vs Muse Glimmer 30B vs Nemotron 3.5 Lightning 30B A3B
MAI-Code-1.1-Flash comes out ahead, 56 to 52 and 42 on our weighted score.
- Our pick
Microsoft
MAI-Code-1.1-Flash
56/100- ECI—
- Price—
- Context256K
Meta
Muse Glimmer 30B
52/100- ECI—
- Price$0.30 / $1.20
- Context131K
NVIDIA
Nemotron 3.5 Lightning 30B A3B
42/100- ECI—
- Price$0.05 / $0.20
- Context262K
MAI-Code-1.1-Flash is our pick
MAI-Code-1.1-Flash is the better all-round choice, scoring 56/100 against Muse Glimmer 30B (52) and Nemotron 3.5 Lightning 30B A3B (42). The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceNemotron 3.5 Lightning 30B A3BNemotron 3.5 Lightning 30B A3B $0.087 · Muse Glimmer 30B $0.525 per 1M tokens (3:1 blend) · MAI-Code-1.1-Flash unpriced
- Longest contextNemotron 3.5 Lightning 30B A3BNemotron 3.5 Lightning 30B A3B 262,144 · MAI-Code-1.1-Flash 256,000 · Muse Glimmer 30B 131,072 tokens
- Widest inputsMAI-Code-1.1-Flash and Muse Glimmer 30BMAI-Code-1.1-Flash: Text, Images · Muse Glimmer 30B: Text, Images · Nemotron 3.5 Lightning 30B A3B: Text
- Self-hostingMuse Glimmer 30B and Nemotron 3.5 Lightning 30B A3BPublishes downloadable weights (Apache 2.0)
| Measure | Weight | MAI-Code-1.1-Flash | Muse Glimmer 30B | Nemotron 3.5 Lightning 30B A3B |
|---|---|---|---|---|
| Inputs & features | 60% | 70 | 70 | 45 |
| Context window | 40% | 36 | 24 | 37 |
| Overall | 100% | 56/100 | 52/100 | 42/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $0.30 | $0.05 (best) |
| Output | — | $1.20 | $0.20 (best) |
| Cached input | — | — | — |
| Blended (3:1) | — | $0.525 | $0.087 (best) |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Median of 10 providers | Median of 9 providers |
| Limits | |||
| Context window | 256,000 tokens | 131,072 tokens | 262,144 tokens (best) |
| Max output | 128,000 tokens | 131,072 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | OpenApache 2.0 | Open |
| API model ID | — | — | nvidia/nemotron-3.5-lightning-30b-a3b |
| API providers | — | 12 | 12 |
| Released | Aug 11, 2026 | Aug 10, 2026 | Aug 11, 2026 |
| Knowledge cutoff | — | Jan 4, 2026 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
MAI-Code-1.1-Flash—
Muse Glimmer 30B$5.40
Nemotron 3.5 Lightning 30B A3B$0.90
Which should you choose?
Which is better: MAI-Code-1.1-Flash, Muse Glimmer 30B or Nemotron 3.5 Lightning 30B A3B?
MAI-Code-1.1-Flash is the better all-round choice, scoring 56/100 against Muse Glimmer 30B (52) and Nemotron 3.5 Lightning 30B A3B (42). The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, MAI-Code-1.1-Flash, Muse Glimmer 30B or Nemotron 3.5 Lightning 30B A3B?
Nemotron 3.5 Lightning 30B A3B is cheaper at $0.05 input / $0.20 output per million tokens (median across 9 API providers; free on Nvidia). Muse Glimmer 30B costs $0.30 input / $1.20 output per million tokens (median across 10 API providers). At a typical mix of three input tokens to one output token, that is $0.087 per million tokens for Nemotron 3.5 Lightning 30B A3B versus $0.525 for Muse Glimmer 30B (6× as much). MAI-Code-1.1-Flash has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MAI-Code-1.1-Flash has not been scored yet, Muse Glimmer 30B has not been scored yet and Nemotron 3.5 Lightning 30B A3B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MAI-Code-1.1-Flash, Muse Glimmer 30B and Nemotron 3.5 Lightning 30B A3B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Nemotron 3.5 Lightning 30B A3B has the largest context window at 262,144 tokens, against 256,000 for MAI-Code-1.1-Flash and 131,072 for Muse Glimmer 30B. Maximum output per response: MAI-Code-1.1-Flash up to 128,000, Muse Glimmer 30B up to 131,072, Nemotron 3.5 Lightning 30B A3B up to 262,144 tokens.
Which can read images, PDFs, audio or video?
MAI-Code-1.1-Flash accepts text and images; Muse Glimmer 30B accepts text and images; Nemotron 3.5 Lightning 30B A3B accepts text. MAI-Code-1.1-Flash handles the widest range of inputs.
Are any of these open source?
Muse Glimmer 30B and Nemotron 3.5 Lightning 30B A3B publishes its weights (Apache 2.0) and can be self-hosted; MAI-Code-1.1-Flash is proprietary.
Which is newer?
MAI-Code-1.1-Flash is the newest, released Aug 11, 2026. Nemotron 3.5 Lightning 30B A3B came out Aug 11, 2026; Muse Glimmer 30B came out Aug 10, 2026. Knowledge cutoff: Muse Glimmer 30B Jan 4, 2026.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.