Inkling vs Qwen3.8 27B vs Qwen3.6 Max Preview
Qwen3.8 27B comes out ahead, 67 to 59 and 54 on our weighted score, and it is the cheaper option too.
Thinking MachinesInkling
59/100- ECI148.6
- Price$3.74 / $9.36
- Context1.05M
- Our pick
Alibaba (Qwen)Qwen3.8 27B
67/100- ECI149.4
- Price$0.40 / $2.50
- Context262K
- Alibaba (Qwen)
Qwen3.6 Max Preview
54/100- ECI149.2
- Price$1.30 / $7.80
- Context262K
Qwen3.8 27B is our pick
Qwen3.8 27B is the better all-round choice, scoring 67/100 against Inkling (59) and Qwen3.6 Max Preview (54). It leads on price and inputs & features. Inkling wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3.8 27BCapabilities Index (ECI): Qwen3.8 27B 149.4 · Qwen3.6 Max Preview 149.2 · Inkling 148.6
- Lowest priceQwen3.8 27BQwen3.8 27B $0.925 · Qwen3.6 Max Preview $2.92 · Inkling $5.14 per 1M tokens (3:1 blend)
- Longest contextInklingInkling 1,048,576 · Qwen3.8 27B 262,144 · Qwen3.6 Max Preview 262,144 tokens
- Widest inputsInkling and Qwen3.8 27BInkling: Text, Images, Audio · Qwen3.8 27B: Text, Images, Video · Qwen3.6 Max Preview: Text
- Self-hostingInkling and Qwen3.8 27BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Inkling | Qwen3.8 27B | Qwen3.6 Max Preview |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 76 | 77 | 77 |
| Price | 25% | 16 | 51 | 28 |
| Inputs & features | 15% | 70 | 80 | 35 |
| Context window | 10% | 61 | 37 | 37 |
| Overall | 100% | 59/100 | 67/100 | 54/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | InklingThinking Machines | Qwen3.8 27BAlibaba (Qwen) | Qwen3.6 Max PreviewAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 148.6 | 149.4 (best) | 149.2 |
| ECI rank | #57 of 148 | #53 of 148 (best) | #54 of 148 |
| GPQA DiamondGraduate-level science questions | 88.3% (best) | — | 87.4% |
| FrontierMath Tiers 1–3Research-level mathematics | 33.3% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 88.9% | — | 91.1% (best) |
| SWE-bench VerifiedFixing real GitHub issues | — | — | 76.7% |
| SimpleQA VerifiedShort factual questions | 40.3% | — | 52.0% (best) |
| Price per million tokens | |||
| Input | $3.74 | $0.40 (best) | $1.30 |
| Output | $9.36 | $2.50 (best) | $7.80 |
| Cached input | $0.748 | — | $0.13 (best) |
| Blended (3:1) | $5.14 | $0.925 (best) | $2.92 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Thinking Machines API | Median of 39 providers | Official Alibaba API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 262,144 tokens | 262,144 tokens |
| Max output | 1,048,576 tokens (best) | 32,768 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | Yes | No |
| Reasoning | Yeslow · medium · high · xhigh · max | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenApache-2.0 | Open | Proprietary |
| API model ID | thinkingmachines/Inkling:peft:262144 | — | qwen3.6-max-preview |
| API providers | 23 | 41 (best) | 10 |
| Released | Jul 15, 2026 | Aug 14, 2026 | Apr 20, 2026 |
| Knowledge cutoff | — | — | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Inkling$56.12
- Qwen3.8 27B$9.00
- Qwen3.6 Max Preview$28.60
Which should you choose?
Which is better: Inkling, Qwen3.8 27B or Qwen3.6 Max Preview?
Qwen3.8 27B is the better all-round choice, scoring 67/100 against Inkling (59) and Qwen3.6 Max Preview (54). It leads on price and inputs & features. Inkling wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Inkling, Qwen3.8 27B or Qwen3.6 Max Preview?
Qwen3.8 27B is cheaper at $0.40 input / $2.50 output per million tokens (median across 39 API providers). Qwen3.6 Max Preview costs $1.30 input / $7.80 output per million tokens (official Alibaba API price); Inkling costs $3.74 input / $9.36 output per million tokens (official Thinking Machines API price). At a typical mix of three input tokens to one output token, that is $0.925 per million tokens for Qwen3.8 27B versus $2.92 for Qwen3.6 Max Preview (3.2× as much) and $5.14 for Inkling (5.6× as much).
Which scores higher on benchmarks?
Qwen3.8 27B scores higher on the Capabilities Index (ECI): Qwen3.8 27B 149.4 (#53 of 148), Qwen3.6 Max Preview 149.2 (#54 of 148) and Inkling 148.6 (#57 of 148). The confidence ranges of the top two overlap (147.5–151.6 vs 147.6–152.0), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Inkling and Qwen3.8 27B yet, so there is no like-for-like coding score. On overall capability, Qwen3.8 27B 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 has the largest context window at 1,048,576 tokens, against 262,144 for Qwen3.8 27B and 262,144 for Qwen3.6 Max Preview. Maximum output per response: Inkling up to 1,048,576, Qwen3.8 27B up to 32,768, Qwen3.6 Max Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Inkling accepts text, images and audio; Qwen3.8 27B accepts text, images and video; Qwen3.6 Max Preview accepts text. Inkling handles the widest range of inputs.
Are any of these open source?
Inkling and Qwen3.8 27B publishes its weights (Apache-2.0) and can be self-hosted; Qwen3.6 Max Preview is proprietary.
Which is newer?
Qwen3.8 27B is the newest, released Aug 14, 2026. Inkling came out Jul 15, 2026; Qwen3.6 Max Preview came out Apr 20, 2026. Knowledge cutoff: Qwen3.6 Max Preview Apr 2025.
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.
