LongCat-2.0 vs Muse Glimmer 30B vs Macaron V1 Tall
Too close to call on our weighted score (Macaron V1 Tall 55, Muse Glimmer 30B 53, LongCat-2.0 53). The right pick depends on what you value most.
Meituan (LongCat)LongCat-2.0
53/100- ECI—
- Price$0.30 / $1.20
- Context1M
MetaMuse Glimmer 30B
53/100- ECI—
- Price$0.30 / $1.20
- Context131K
Mindlab
Macaron V1 Tall
55/100- ECI—
- Price$0.247 / $1.43
- Context262K
Too close to call
It is close. Our weighted score puts them within 2 points (Macaron V1 Tall 55/100, Muse Glimmer 30B 53/100, LongCat-2.0 53/100), so choose by what matters most for your work: LongCat-2.0 on price and LongCat-2.0 for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. 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 priceLongCat-2.0 and Muse Glimmer 30BLongCat-2.0 $0.525 · Muse Glimmer 30B $0.525 · Macaron V1 Tall $0.543 per 1M tokens (3:1 blend)
- Longest contextLongCat-2.0LongCat-2.0 1,000,000 · Macaron V1 Tall 262,144 · Muse Glimmer 30B 131,072 tokens
- Widest inputsMuse Glimmer 30B and Macaron V1 TallLongCat-2.0: Text · Muse Glimmer 30B: Text, Images · Macaron V1 Tall: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | LongCat-2.0 | Muse Glimmer 30B | Macaron V1 Tall |
|---|---|---|---|---|
| Price | 50% | 60 | 60 | 60 |
| Inputs & features | 30% | 35 | 60 | 60 |
| Context window | 20% | 60 | 25 | 37 |
| Overall | 100% | 53/100 | 53/100 | 55/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | LongCat-2.0Meituan (LongCat) | Muse Glimmer 30BMeta | Macaron V1 TallMindlab |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.30 | $0.30 | $0.247 (best) |
| Output | $1.20 (best) | $1.20 (best) | $1.43 |
| Cached input | $0.006 | — | — |
| Blended (3:1) | $0.525 (best) | $0.525 (best) | $0.543 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official LongCat API | Median of 11 providers | Median of 1 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 131,072 tokens | 262,144 tokens |
| Max output | 131,072 tokens (best) | 131,072 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | OpenApache 2.0 | OpenMIT |
| API model ID | LongCat-2.0 | — | — |
| API providers | 7 | 13 (best) | 1 |
| Released | Jun 30, 2026 | Aug 10, 2026 | Jul 21, 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.
- LongCat-2.0$5.40
- Muse Glimmer 30B$5.40
- Macaron V1 Tall$5.33
Which should you choose?
Which is better: LongCat-2.0, Muse Glimmer 30B or Macaron V1 Tall?
It is close. Our weighted score puts them within 2 points (Macaron V1 Tall 55/100, Muse Glimmer 30B 53/100, LongCat-2.0 53/100), so choose by what matters most for your work: LongCat-2.0 on price and LongCat-2.0 for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, LongCat-2.0, Muse Glimmer 30B or Macaron V1 Tall?
LongCat-2.0 is cheaper at $0.30 input / $1.20 output per million tokens (official LongCat API price). Muse Glimmer 30B costs $0.30 input / $1.20 output per million tokens (median across 11 API providers); Macaron V1 Tall costs $0.247 input / $1.43 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.525 per million tokens for LongCat-2.0 versus $0.525 for Muse Glimmer 30B (1× as much) and $0.543 for Macaron V1 Tall (1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. LongCat-2.0 has not been scored yet, Muse Glimmer 30B has not been scored yet and Macaron V1 Tall has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for LongCat-2.0, Muse Glimmer 30B and Macaron V1 Tall 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?
LongCat-2.0 has the largest context window at 1,000,000 tokens, against 262,144 for Macaron V1 Tall and 131,072 for Muse Glimmer 30B. Maximum output per response: LongCat-2.0 up to 131,072, Muse Glimmer 30B up to 131,072, Macaron V1 Tall up to 32,768 tokens.
Which can read images, PDFs, audio or video?
LongCat-2.0 accepts text; Muse Glimmer 30B accepts text and images; Macaron V1 Tall accepts text and images. Muse Glimmer 30B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0 and MIT), so you can self-host them.
Which is newer?
Muse Glimmer 30B is the newest, released Aug 10, 2026. Macaron V1 Tall came out Jul 21, 2026; LongCat-2.0 came out Jun 30, 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 Nov 2, 2026.
