GLM 5.3 Flash vs GPT-5.6 Terra
Compare GLM 5.3 Flash and GPT-5.6 Terra side-by-side. See how these vision models stack up in Image Captioning, OCR, Classification, Object Detection, and Open Prompt.
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Models in this comparison
GLM 5.3 Flash vs GPT-5.6 Terra on Vision Evals
GLM 5.3 Flash scores higher on 3 of the six Vision Evals tasks.
The widest gap is Object Detection, where GPT-5.6 Terra leads 60.7% to 33.1%.
Overall, GLM 5.3 Flash averages 66.3% (#22 of 33) against 72.4% (#13 of 33) for GPT-5.6 Terra.
GLM 5.3 Flash is both cheaper ($0.0002 vs $0.0089 per sample) and faster (6.8s vs 7.2s per sample).
GLM 5.3 Flash vs GPT-5.6 Terra Comparison Table
Evals updated August 26, 2026Pricing updated August 26, 2026
| Property | GLM 5.3 Flash | GPT-5.6 Terra |
|---|---|---|
| Organization | Z.ai | OpenAI |
| Category | open | closed |
| Modality | multimodal | multimodal |
| Release Date | Aug 2026 | Jul 2026 |
| Context Window | 1.0M | 1.1M |
| Parameters | 320B total, 18B active | |
| License | MIT | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | |
| Output $/1M | $12.00 | |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | Demo |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 66.3% | 72.4% |
| Avg cost / sample | $0.0002 | $0.0089 |
| Avg speed / sample | 6.78s | 7.15s |
| By task | ||
| Object Detection | 33.1% $0.0004 | 60.7% $0.014 |
| Counting | 55.4% $0.0001 | 67.6% $0.0060 |
| Identification | 84.4% $0.0001 | 78.1% $0.0039 |
| OCR | 90.6% $0.0002 | 88.8% $0.013 |
| Data Extraction | 83.5% $0.0001 | 79.4% $0.0037 |
| Reasoning (low) | 51.0% $0.0001 | 59.6% $0.0050 |
| Reasoning (high) | 59.6% $0.0001 | 64.2% $0.0066 |
GLM 5.3 Flash vs GPT-5.6 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. Z.ai reports scores of 84.3 on Terminal-Bench 2.1, 63.4 on DeepSWE 1.1, 55.3 on Humanity's Last Exam with tools, and 48.8 on AutomationBench, and the model exposes low, high, and max thinking modes.
GPT-5.6 Terra is the mid-tier reasoning model in OpenAI's GPT-5.6 family, which also includes the flagship Sol and the lightweight Luna. Introduced in a limited preview on June 26, 2026, and made broadly available on July 9, 2026, Terra accepts text and image input and produces text output, supporting vision, function calling, tool use, and agentic workflows. It is designed as a balanced option for everyday professional and production workloads — including coding assistance, document analysis, customer support, and multi-step agent tasks — where both output quality and cost efficiency matter. OpenAI positions Terra as delivering performance competitive with GPT-5.5 at approximately half the price, with a context window of around 1,050,000 tokens. On Terminal-Bench 2.1, Terra scores 84.3%, matching Claude Fable 5 on that benchmark. Under OpenAI's Preparedness Framework, Terra is rated High for cybersecurity and biological capabilities, meaning it demonstrates meaningful capability in those domains without reaching the Critical threshold.
GPT-5.6 introduces a new naming convention in which the generation number (5.6) is paired with a durable capability tier name (Sol, Terra, or Luna), allowing each tier to advance on its own schedule. Terra carries the API identifier gpt-5.6-terra and supports the same reasoning effort controls available across the family, including adjustable reasoning depth. The model includes prompt caching with explicit cache breakpoints and a 30-minute minimum cache life, with cache writes billed at 1.25x the uncached input rate and cache reads receiving a 90% discount. GPT-5.6 Terra is a proprietary, closed-weights model served through the OpenAI API, Codex, and ChatGPT.
Frequently Asked Questions
On Roboflow's Vision Evals, GPT-5.6 Terra performed slightly better overall. The two split the six vision tasks 3 to 3, but GPT-5.6 Terra averages 72.4% (#13 of 33) against 66.3% (#22 of 33) for GLM 5.3 Flash. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Object Detection benchmark, GPT-5.6 Terra leads with 60.7% against 33.1%. This is the widest gap between the two models across the benchmark's tasks.
GLM 5.3 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0002 per sample against $0.0089. Actual costs depend on your image sizes, prompts, and output length.
GLM 5.3 Flash is faster. Across Roboflow's Vision Evals it averaged 6.8s per inference against 7.2s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.
Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.