GLM 5.3 Flash vs GPT-6.1 Terra
GPT-6.1 Terra and GLM 5.3 Flash score 85.8% vs 55.8% averaged across five Vision Evals tasks (#2 and #46 of 65 models), so GPT-6.1 Terra leads overall.
- GPT-6.1 Terra wins all 5 tasks, with its widest lead on object detection (84.7% vs 33.1%).
- GLM 5.3 Flash is about a fifth of the cost: $0.0006 vs $0.0033 overall average cost per sample.
- GLM 5.3 Flash is faster: 9.3s vs 10.1s per sample.
Roboflow Vision Evals. Full breakdown below.
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GLM 5.3 Flash vs GPT-6.1 Terra on Vision Evals
Roboflow Vision Evals. Full breakdown below.
GLM 5.3 Flash vs GPT-6.1 Terra Comparison Table
Evals updated October 26, 2026Pricing updated November 7, 2026
| Property | GLM 5.3 Flash | GPT-6.1 Terra |
|---|---|---|
| Organization | Z.ai | OpenAI |
| Category | open | closed |
| Modality | multimodal | multimodal |
| Release Date | Aug 2026 | Oct 2026 |
| Context Window | 1.0M | 1.1M |
| Parameters | 320B total, 18B active | undisclosed |
| License | MIT | Proprietary |
| Commercial use | free for commercial use | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $0.150 | $1.00 |
| Output $/1M | $0.500 | $5.00 |
| Vision Tasks | ||
| Promptable Concept Segmentation | Not listed | Demo |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 55.8% | 85.8% |
| Avg cost / sample | $0.0006 | $0.0033 |
| Avg speed / sample | 9.29s | 10.05s |
| By task | ||
| Object Detection (low) | 33.1% | 84.7% ±0.1, Mean of 3 runs, range 84.7 to 84.8 |
| Object Detection (high) | – | 84.7% ±0.4, Mean of 3 runs, range 84.2 to 84.9 |
| Counting (low) | 55.4% | 80.2% ±2.0, Mean of 3 runs, range 78.4 to 82.4 |
| Counting (high) | – | 84.2% ±3.4, Mean of 3 runs, range 81.1 to 87.8 |
| Identification (low) | 84.4% | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| Identification (high) | – | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| OCR (low) | 55.4% | 81.9% |
| by category |
|
|
| OCR (high) | 55.3% | 84.4% |
| by category |
|
|
| Reasoning (low) | 51.0% | 85.4% ±1.7, Mean of 3 runs, range 83.4 to 86.8 |
| Reasoning (high) | 59.6% | 87.0% ±1.3, Mean of 3 runs, range 85.4 to 88.1 |
GLM 5.3 Flash vs GPT-6.1 Terra: Overview
GLM-5.3-Flash is the first natively multimodal model in Z.ai's GLM-5 series, a mixture-of-experts transformer with roughly 320 billion total parameters and 18 billion activated per token. It routes each token through 8 of 288 experts across 45 language layers that interleave KDA linear attention with sparse multi-head latent attention, and pairs them with a 24-layer vision encoder that handles image and video input. The checkpoint declares a maximum context length of 1,048,576 tokens, ships in native FP8, and includes a multi-token prediction draft layer for speculative decoding. Z.ai reports that the hybrid attention design reduces attention computation by 3.01x and KV cache size by 4.44x relative to GLM-5.3.
The model starts from a newly trained base built on a 30 trillion token multimodal pre-training corpus and adopts Manifold-Constrained Hyper-Connections to improve scaling efficiency. Vision is integrated into the coding and agent loop, so the model can inspect interfaces, rendered output, and images while operating across code, browsers, and graphical user interfaces.
GPT-6.1 Terra is an OpenAI model released on October 26, 2026 for visual reasoning, computer use and writing. It accepts text and image inputs and produces text, with a 1,050,000-token context window and up to 128,000 output tokens. OpenAI lists applications including matching product photographs to catalog entries, interpreting technical drawings and operating application screens.
The API exposes six reasoning effort settings: none, low, medium, high, xhigh and max. Medium is the default. The model supports structured outputs and tool calling through the Responses API. Vision Evals reports its Low and High results for text understanding, counting, identification, reasoning and object detection, using native OpenAI API inference. Terra is a proprietary model; its weights are not released.