Inkling Small vs Muse Spark 1.2 vs Qwen3.8 27B
Too close to call on our weighted score (Muse Spark 1.2 72, Inkling Small 70, Qwen3.8 27B 67). The right pick depends on what you value most.
Thinking MachinesInkling Small
70/100- ECI150.2
- Price$0.50 / $1.20
- Context1.05M
MetaMuse Spark 1.2
72/100- ECI155.0
- Price$1.25 / $4.25
- Context1.05M
Alibaba (Qwen)Qwen3.8 27B
67/100- ECI149.4
- Price$0.40 / $2.50
- Context262K
Too close to call
It is close. Our weighted score puts them within 2 points (Muse Spark 1.2 72/100, Inkling Small 70/100, Qwen3.8 27B 67/100), so choose by what matters most for your work: Muse Spark 1.2 for raw capability and Inkling Small on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMuse Spark 1.2Capabilities Index (ECI): Muse Spark 1.2 155.0 · Inkling Small 150.2 · Qwen3.8 27B 149.4
- Lowest priceInkling SmallInkling Small $0.675 · Qwen3.8 27B $0.925 · Muse Spark 1.2 $2.00 per 1M tokens (3:1 blend)
- Longest contextInkling Small and Muse Spark 1.2Inkling Small 1,048,576 · Muse Spark 1.2 1,048,576 · Qwen3.8 27B 262,144 tokens
- Widest inputsMuse Spark 1.2Inkling Small: Text, Images, Audio · Muse Spark 1.2: Text, Images, PDFs, Audio, Video · Qwen3.8 27B: Text, Images, Video
- Self-hostingInkling Small and Qwen3.8 27BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Inkling Small | Muse Spark 1.2 | Qwen3.8 27B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 84 | 77 |
| Price | 25% | 58 | 36 | 51 |
| Inputs & features | 15% | 70 | 100 | 80 |
| Context window | 10% | 61 | 61 | 37 |
| Overall | 100% | 70/100 | 72/100 | 67/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Inkling SmallThinking Machines | Muse Spark 1.2Meta | Qwen3.8 27BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 150.2 | 155.0 (best) | 149.4 |
| ECI rank | #47 of 148 | #30 of 148 (best) | #53 of 148 |
| GPQA DiamondGraduate-level science questions | 88.5% | — | — |
| FrontierMath Tiers 1–3Research-level mathematics | 46.3% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 90.0% | — | — |
| SimpleQA VerifiedShort factual questions | 19.1% | 60.3% (best) | — |
| Price per million tokens | |||
| Input | $0.50 | $1.25 | $0.40 (best) |
| Output | $1.20 (best) | $4.25 | $2.50 |
| Cached input | — | $0.15 | — |
| Blended (3:1) | $0.675 (best) | $2.00 | $0.925 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Official Meta API | Median of 39 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 1,048,576 tokens (best) | 262,144 tokens |
| Max output | 1,048,576 tokens (best) | 131,072 tokens | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | Yes | Yes | No |
| Video | No | Yes | Yes |
| Reasoning | Yes | Yesminimal · low · medium · high · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | Open |
| API model ID | — | muse-spark-1.2 | — |
| API providers | 11 | 15 | 41 (best) |
| Released | Jul 30, 2026 | Aug 5, 2026 | Aug 14, 2026 |
| Knowledge cutoff | — | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Inkling Small$7.40
- Muse Spark 1.2$21.00
- Qwen3.8 27B$9.00
Which should you choose?
Which is better: Inkling Small, Muse Spark 1.2 or Qwen3.8 27B?
It is close. Our weighted score puts them within 2 points (Muse Spark 1.2 72/100, Inkling Small 70/100, Qwen3.8 27B 67/100), so choose by what matters most for your work: Muse Spark 1.2 for raw capability and Inkling Small on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Inkling Small, Muse Spark 1.2 or Qwen3.8 27B?
Inkling Small is cheaper at $0.50 input / $1.20 output per million tokens (median across 11 API providers). Qwen3.8 27B costs $0.40 input / $2.50 output per million tokens (median across 39 API providers); Muse Spark 1.2 costs $1.25 input / $4.25 output per million tokens (official Meta API price). At a typical mix of three input tokens to one output token, that is $0.675 per million tokens for Inkling Small versus $0.925 for Qwen3.8 27B (1.4× as much) and $2.00 for Muse Spark 1.2 (3× as much).
Which scores higher on benchmarks?
Muse Spark 1.2 scores higher on the Capabilities Index (ECI): Muse Spark 1.2 155.0 (#30 of 148), Inkling Small 150.2 (#47 of 148) and Qwen3.8 27B 149.4 (#53 of 148). Their confidence ranges do not overlap (152.8–157.5 vs 147.5–152.1), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for Inkling Small, Muse Spark 1.2 and Qwen3.8 27B yet, so there is no like-for-like coding score. On overall capability, Muse Spark 1.2 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Inkling Small and Muse Spark 1.2 have the largest context windows (1,048,576 and 1,048,576 tokens), against 262,144 for Qwen3.8 27B. Maximum output per response: Inkling Small up to 1,048,576, Muse Spark 1.2 up to 131,072, Qwen3.8 27B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Inkling Small accepts text, images and audio; Muse Spark 1.2 accepts text, images, PDFs, audio and video; Qwen3.8 27B accepts text, images and video. Muse Spark 1.2 handles the widest range of inputs.
Are any of these open source?
Inkling Small and Qwen3.8 27B publishes its weights (Apache-2.0) and can be self-hosted; Muse Spark 1.2 is proprietary.
Which is newer?
Qwen3.8 27B is the newest, released Aug 14, 2026. Muse Spark 1.2 came out Aug 5, 2026; Inkling Small came out Jul 30, 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.
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