GLM-5.1 vs Inkling
Too close to call on our weighted score (Inkling 59, GLM-5.1 57). The right pick depends on what you value most.
Too close to call
It is close. Our weighted score puts them within 1 points (Inkling 59/100, GLM-5.1 57/100), so choose by what matters most for your work: GLM-5.1 for raw capability and Inkling for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGLM-5.1Capabilities Index (ECI): GLM-5.1 149.9 · Inkling 148.6
- Lowest priceGLM-5.1GLM-5.1 $2.15 · Inkling $5.14 per 1M tokens (3:1 blend)
- Longest contextInklingInkling 1,048,576 · GLM-5.1 200,000 tokens
- Widest inputsInklingGLM-5.1: Text · Inkling: Text, Images, Audio
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-5.1 | Inkling |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 76 |
| Price | 25% | 34 | 16 |
| Inputs & features | 15% | 45 | 70 |
| Context window | 10% | 32 | 61 |
| Overall | 100% | 57/100 | 59/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification |  GLM-5.1Z.ai (Zhipu) |  InklingThinking Machines |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 149.9 (best) | 148.6 |
| ECI rank | #51 of 148 (best) | #57 of 148 |
| GPQA DiamondGraduate-level science questions | 89.9% (best) | 88.3% |
| FrontierMath Tiers 1–3Research-level mathematics | 36.8% (best) | 33.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.3% (best) | 88.9% |
| SWE-bench VerifiedFixing real GitHub issues | 74.2% | — |
| SimpleQA VerifiedShort factual questions | 34.0% | 40.3% (best) |
| Price per million tokens | ||
| Input | $1.40 (best) | $3.74 |
| Output | $4.40 (best) | $9.36 |
| Cached input | $0.26 (best) | $0.748 |
| Blended (3:1) | $2.15 (best) | $5.14 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Thinking Machines API |
| Limits | ||
| Context window | 200,000 tokens | 1,048,576 tokens (best) |
| Max output | 131,072 tokens | 1,048,576 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | Yes |
| Video | No | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | OpenApache-2.0 |
| API model ID | glm-5.1 | thinkingmachines/Inkling:peft:262144 |
| API providers | 40 (best) | 23 |
| Released | Apr 7, 2026 | Jul 15, 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.
- GLM-5.1$22.80
- Inkling$56.12
Which should you choose?
Which is better: GLM-5.1 or Inkling?
It is close. Our weighted score puts them within 1 points (Inkling 59/100, GLM-5.1 57/100), so choose by what matters most for your work: GLM-5.1 for raw capability and Inkling for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.1 or Inkling?
GLM-5.1 is cheaper at $1.40 input / $4.40 output per million tokens (official Z.AI 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 $2.15 per million tokens for GLM-5.1 versus $5.14 for Inkling (2.4× as much).
Which scores higher on benchmarks?
GLM-5.1 scores higher on the Capabilities Index (ECI): GLM-5.1 149.9 (#51 of 148) and Inkling 148.6 (#57 of 148). The confidence ranges of the top two overlap (148.0–151.6 vs 145.7–150.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5.1 89.9%, Inkling 88.3%; FrontierMath Tiers 1–3 — GLM-5.1 36.8%, Inkling 33.3%; OTIS Mock AIME 2024–2025 — GLM-5.1 93.3%, Inkling 88.9%; SimpleQA Verified — Inkling 40.3%, GLM-5.1 34.0%.
Which is better for coding?
There are no published SWE-bench Verified results for Inkling yet, so there is no like-for-like coding score. On overall capability, GLM-5.1 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Inkling has the largest context window at 1,048,576 tokens, against 200,000 for GLM-5.1. Maximum output per response: GLM-5.1 up to 131,072, Inkling up to 1,048,576 tokens.
Which can read images, PDFs, audio or video?
GLM-5.1 accepts text; Inkling accepts text, images and audio. Inkling handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Inkling is the newest, released Jul 15, 2026. GLM-5.1 came out Apr 7, 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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