Qwen3.8 27B vs GPT-5.4 mini vs Inkling Small
Inkling Small comes out ahead, 70 to 67 and 63 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen3.8 27B
67/100- ECI149.4
- Price$0.40 / $2.50
- Context262K
OpenAIGPT-5.4 mini
63/100- ECI148.8
- Price$0.75 / $4.50
- Context400K
- Our pick
Thinking MachinesInkling Small
70/100- ECI150.2
- Price$0.50 / $1.20
- Context1.05M
Inkling Small is our pick
Inkling Small is the better all-round choice, scoring 70/100 against Qwen3.8 27B (67) and GPT-5.4 mini (63). It leads on price and context window. Qwen3.8 27B wins on inputs & features. 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 · GPT-5.4 mini 148.8
- Lowest priceInkling SmallInkling Small $0.675 · Qwen3.8 27B $0.925 · GPT-5.4 mini $1.69 per 1M tokens (3:1 blend)
- Longest contextInkling SmallInkling Small 1,048,576 · GPT-5.4 mini 400,000 · Qwen3.8 27B 262,144 tokens
- Widest inputsQwen3.8 27B and Inkling SmallQwen3.8 27B: Text, Images, Video · GPT-5.4 mini: Text, Images · Inkling Small: Text, Images, Audio
- Self-hostingQwen3.8 27B and Inkling SmallPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Qwen3.8 27B | GPT-5.4 mini | Inkling Small |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 77 | 77 | 78 |
| Price | 25% | 51 | 39 | 58 |
| Inputs & features | 15% | 80 | 70 | 70 |
| Context window | 10% | 37 | 44 | 61 |
| Overall | 100% | 67/100 | 63/100 | 70/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3.8 27BAlibaba (Qwen) | GPT-5.4 miniOpenAI | Inkling SmallThinking Machines |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 149.4 | 148.8 | 150.2 (best) |
| ECI rank | #53 of 148 | #56 of 148 | #47 of 148 (best) |
| GPQA DiamondGraduate-level science questions | — | 86.9% | 88.5% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | 51.2% (best) | 46.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 88.9% | 90.0% (best) |
| SimpleQA VerifiedShort factual questions | — | 29.4% (best) | 19.1% |
| Price per million tokens | |||
| Input | $0.40 (best) | $0.75 | $0.50 |
| Output | $2.50 | $4.50 | $1.20 (best) |
| Cached input | — | $0.075 | — |
| Blended (3:1) | $0.925 | $1.69 | $0.675 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 39 providers | Official OpenAI API | Median of 11 providers |
| Limits | |||
| Context window | 262,144 tokens | 400,000 tokens | 1,048,576 tokens (best) |
| Max output | 32,768 tokens | 128,000 tokens | 1,048,576 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | Yes |
| Video | Yes | No | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | OpenApache-2.0 |
| API model ID | — | gpt-5.4-mini | — |
| API providers | 41 (best) | 29 | 11 |
| Released | Aug 14, 2026 | Mar 17, 2026 | Jul 30, 2026 |
| Knowledge cutoff | — | Aug 31, 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3.8 27B$9.00
- GPT-5.4 mini$16.50
- Inkling Small$7.40
Which should you choose?
Which is better: Qwen3.8 27B, GPT-5.4 mini or Inkling Small?
Inkling Small is the better all-round choice, scoring 70/100 against Qwen3.8 27B (67) and GPT-5.4 mini (63). It leads on price and context window. Qwen3.8 27B wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3.8 27B, GPT-5.4 mini or Inkling Small?
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); GPT-5.4 mini costs $0.75 input / $4.50 output per million tokens (official OpenAI 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 $1.69 for GPT-5.4 mini (2.5× 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 GPT-5.4 mini 148.8 (#56 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 Qwen3.8 27B, GPT-5.4 mini and Inkling Small 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 has the largest context window at 1,048,576 tokens, against 400,000 for GPT-5.4 mini and 262,144 for Qwen3.8 27B. Maximum output per response: Qwen3.8 27B up to 32,768, GPT-5.4 mini up to 128,000, Inkling Small up to 1,048,576 tokens.
Which can read images, PDFs, audio or video?
Qwen3.8 27B accepts text, images and video; GPT-5.4 mini accepts text and images; Inkling Small accepts text, images and audio. Qwen3.8 27B handles the widest range of inputs.
Are any of these open source?
Qwen3.8 27B and Inkling Small publishes its weights (Apache-2.0) and can be self-hosted; GPT-5.4 mini is proprietary.
Which is newer?
Qwen3.8 27B is the newest, released Aug 14, 2026. Inkling Small came out Jul 30, 2026; GPT-5.4 mini came out Mar 17, 2026. Knowledge cutoff: GPT-5.4 mini Aug 31, 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.
