Step 3.7 Flash vs Muse Glimmer 30B vs Perceptron Mk1
Step 3.7 Flash comes out ahead, 63 to 53 and 45 on our weighted score, and it is the cheaper option too.
- Our pick
StepFunStep 3.7 Flash
63/100- ECI—
- Price$0.20 / $1.15
- Context256K
MetaMuse Glimmer 30B
53/100- ECI—
- Price$0.30 / $1.20
- Context131K
Perceptron
Perceptron Mk1
45/100- ECI—
- Price$0.15 / $1.50
- Context33K
Step 3.7 Flash is our pick
Step 3.7 Flash is the better all-round choice, scoring 63/100 against Muse Glimmer 30B (53) and Perceptron Mk1 (45). It leads on price, inputs & features and context window. 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 priceStep 3.7 FlashStep 3.7 Flash $0.438 · Perceptron Mk1 $0.487 · Muse Glimmer 30B $0.525 per 1M tokens (3:1 blend)
- Longest contextStep 3.7 FlashStep 3.7 Flash 256,000 · Muse Glimmer 30B 131,072 · Perceptron Mk1 32,768 tokens
- Widest inputsStep 3.7 Flash and Perceptron Mk1Step 3.7 Flash: Text, Images, Video · Muse Glimmer 30B: Text, Images · Perceptron Mk1: Text, Images, Video
- Self-hostingStep 3.7 Flash and Muse Glimmer 30BPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Step 3.7 Flash | Muse Glimmer 30B | Perceptron Mk1 |
|---|---|---|---|---|
| Price | 50% | 64 | 60 | 62 |
| Inputs & features | 30% | 80 | 60 | 45 |
| Context window | 20% | 36 | 25 | 0 |
| Overall | 100% | 63/100 | 53/100 | 45/100 |
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 | Step 3.7 FlashStepFun | Muse Glimmer 30BMeta | Perceptron Mk1Perceptron |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 | $0.30 | $0.15 (best) |
| Output | $1.15 (best) | $1.20 | $1.50 |
| Cached input | $0.04 | — | — |
| Blended (3:1) | $0.438 (best) | $0.525 | $0.487 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official StepFun (Global) API | Median of 11 providers | Median of 3 providers |
| Limits | |||
| Context window | 256,000 tokens (best) | 131,072 tokens | 32,768 tokens |
| Max output | 256,000 tokens (best) | 131,072 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | Yes |
| Reasoning | Yeslow · medium · high | Yes | Yes |
| Tool calling | Yes | Yes | No |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Proprietary |
| API model ID | step-3.7-flash | — | — |
| API providers | 19 (best) | 13 | 3 |
| Released | May 29, 2026 | Aug 10, 2026 | May 12, 2026 |
| Knowledge cutoff | Mar 1, 2026 | 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.
- Step 3.7 Flash$4.30
- Muse Glimmer 30B$5.40
- Perceptron Mk1$4.50
Which should you choose?
Which is better: Step 3.7 Flash, Muse Glimmer 30B or Perceptron Mk1?
Step 3.7 Flash is the better all-round choice, scoring 63/100 against Muse Glimmer 30B (53) and Perceptron Mk1 (45). It leads on price, inputs & features and context window. 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, Step 3.7 Flash, Muse Glimmer 30B or Perceptron Mk1?
Step 3.7 Flash is cheaper at $0.20 input / $1.15 output per million tokens (official StepFun (Global) API price). Perceptron Mk1 costs $0.15 input / $1.50 output per million tokens (median across 3 API providers); Muse Glimmer 30B costs $0.30 input / $1.20 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.438 per million tokens for Step 3.7 Flash versus $0.487 for Perceptron Mk1 (1.1× as much) and $0.525 for Muse Glimmer 30B (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Step 3.7 Flash has not been scored yet, Muse Glimmer 30B has not been scored yet and Perceptron Mk1 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Step 3.7 Flash, Muse Glimmer 30B and Perceptron Mk1 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Perceptron Mk1 does not support tool calling, which most coding agents need.
Which has the bigger context window?
Step 3.7 Flash has the largest context window at 256,000 tokens, against 131,072 for Muse Glimmer 30B and 32,768 for Perceptron Mk1. Maximum output per response: Step 3.7 Flash up to 256,000, Muse Glimmer 30B up to 131,072, Perceptron Mk1 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Step 3.7 Flash accepts text, images and video; Muse Glimmer 30B accepts text and images; Perceptron Mk1 accepts text, images and video. Step 3.7 Flash handles the widest range of inputs.
Are any of these open source?
Step 3.7 Flash and Muse Glimmer 30B publishes its weights (Apache 2.0) and can be self-hosted; Perceptron Mk1 is proprietary.
Which is newer?
Muse Glimmer 30B is the newest, released Aug 10, 2026. Step 3.7 Flash came out May 29, 2026; Perceptron Mk1 came out May 12, 2026. Knowledge cutoff: Step 3.7 Flash Mar 1, 2026, 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.
