Inkling Small vs Qwen3.8 27B vs MiniMax-M3
Too close to call on our weighted score (Inkling Small 70, MiniMax-M3 69, Qwen3.8 27B 67). The right pick depends on what you value most.
Thinking Machines
Inkling Small
70/100- ECI150.2
- Price$0.50 / $1.20
- Context1.05M
Alibaba (Qwen)
Qwen3.8 27B
67/100- ECI149.4
- Price$0.40 / $2.50
- Context262K
MiniMax
MiniMax-M3
69/100- ECI147.0
- Price$0.30 / $1.20
- Context1.05M
Too close to call
It is close. Our weighted score puts them within a point (Inkling Small 70/100, MiniMax-M3 69/100, Qwen3.8 27B 67/100), so choose by what matters most for your work: Inkling Small for raw capability and MiniMax-M3 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityInkling SmallCapabilities Index (ECI): Inkling Small 150.2 · Qwen3.8 27B 149.4 · MiniMax-M3 147.0
- Lowest priceMiniMax-M3MiniMax-M3 $0.525 · Inkling Small $0.675 · Qwen3.8 27B $0.925 per 1M tokens (3:1 blend)
- Longest contextInkling Small and MiniMax-M3Inkling Small 1,048,576 · MiniMax-M3 1,048,576 · Qwen3.8 27B 262,144 tokens
- Widest inputsSame inputsInkling Small: Text, Images, Audio · Qwen3.8 27B: Text, Images, Video · MiniMax-M3: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Inkling Small | Qwen3.8 27B | MiniMax-M3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 77 | 74 |
| Price | 25% | 58 | 51 | 63 |
| Inputs & features | 15% | 70 | 80 | 70 |
| Context window | 10% | 61 | 37 | 61 |
| Overall | 100% | 70/100 | 67/100 | 69/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 150.2 (best) | 149.4 | 147.0 |
| ECI rank | #47 of 148 (best) | #53 of 148 | #62 of 148 |
| GPQA DiamondGraduate-level science questions | 88.5% | — | 90.9% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 46.3% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 90.0% (best) | — | 71.1% |
| SimpleQA VerifiedShort factual questions | 19.1% | — | — |
| Price per million tokens | |||
| Input | $0.50 | $0.40 | $0.30 (best) |
| Output | $1.20 (best) | $2.50 | $1.20 (best) |
| Cached input | — | — | $0.06 |
| Blended (3:1) | $0.675 | $0.925 | $0.525 (best) |
| Long-context rate | Same rate | Same rate | Over 512K: $0.60 / $2.40 |
| Price source | Median of 11 providers | Median of 39 providers | Official MiniMax (minimax.io) API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 262,144 tokens | 1,048,576 tokens (best) |
| Max output | 1,048,576 tokens (best) | 32,768 tokens | 512,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | Yes | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenApache-2.0 | Open | Open |
| API model ID | — | — | MiniMax-M3 |
| API providers | 11 | 41 | 42 (best) |
| Released | Jul 30, 2026 | Aug 14, 2026 | Jun 1, 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
Qwen3.8 27B$9.00
MiniMax-M3$5.40
Which should you choose?
Which is better: Inkling Small, Qwen3.8 27B or MiniMax-M3?
It is close. Our weighted score puts them within a point (Inkling Small 70/100, MiniMax-M3 69/100, Qwen3.8 27B 67/100), so choose by what matters most for your work: Inkling Small for raw capability and MiniMax-M3 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Inkling Small, Qwen3.8 27B or MiniMax-M3?
MiniMax-M3 is cheaper at $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). Inkling Small costs $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). At a typical mix of three input tokens to one output token, that is $0.525 per million tokens for MiniMax-M3 versus $0.675 for Inkling Small (1.3× as much) and $0.925 for Qwen3.8 27B (1.8× as much).
Which scores higher on benchmarks?
Inkling Small scores higher on the Capabilities Index (ECI): Inkling Small 150.2 (#47 of 148), Qwen3.8 27B 149.4 (#53 of 148) and MiniMax-M3 147.0 (#62 of 148). The confidence ranges of the top two overlap (147.5–152.1 vs 147.5–151.6), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Inkling Small, Qwen3.8 27B and MiniMax-M3 yet, so there is no like-for-like coding score. On overall capability, Inkling Small 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 MiniMax-M3 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, Qwen3.8 27B up to 32,768, MiniMax-M3 up to 512,000 tokens.
Which can read images, PDFs, audio or video?
Inkling Small accepts text, images and audio; Qwen3.8 27B accepts text, images and video; MiniMax-M3 accepts text, images and video. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Qwen3.8 27B is the newest, released Aug 14, 2026. Inkling Small came out Jul 30, 2026; MiniMax-M3 came out Jun 1, 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.