DeepSeek V3.1 vs GLM-5
DeepSeek V3.1 (2026) and GLM-5 (2026) are frontier reasoning models from DeepSeek and Zhipu AI. DeepSeek V3.1 ships a 64K-token context window, while GLM-5 ships a 200k-token context window. On SWE-bench Verified, GLM-5 leads by 11.8 pts. On pricing, DeepSeek V3.1 costs $0.56/1M input tokens versus $0.72/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
DeepSeek V3.1 is safer overall; choose GLM-5 when reasoning depth matters.
Specs
| Released | 2026-03-01 | 2026-02-11 |
| Context window | 64K | 200k |
| Parameters | — | 744B total, 40B active |
| Architecture | mixture of experts | mixture of experts |
| License | Open Source | MIT |
| Knowledge cutoff | - | - |
Pricing and availability
| DeepSeek V3.1 | GLM-5 | |
|---|---|---|
| Input price | $0.56/1M tokens | $0.72/1M tokens |
| Output price | $1.68/1M tokens | $2.3/1M tokens |
| Providers |
Capabilities
| DeepSeek V3.1 | GLM-5 | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | DeepSeek V3.1 | GLM-5 |
|---|---|---|
| SWE-bench Verified | 66.0 | 77.8 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has DeepSeek V3.1 at 66 and GLM-5 at 77.8, with GLM-5 ahead by 11.8 points. The largest visible gap is 11.8 points on SWE-bench Verified, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: DeepSeek V3.1, multimodal input: DeepSeek V3.1, reasoning mode: GLM-5, function calling: GLM-5, tool use: GLM-5, and code execution: DeepSeek V3.1. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, DeepSeek V3.1 lists $0.56/1M input and $1.68/1M output tokens, while GLM-5 lists $0.72/1M input and $2.3/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3.1 lower by about $0.3 per million blended tokens. Availability is 6 providers versus 5, so concentration risk also matters.
Choose DeepSeek V3.1 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose GLM-5 when reasoning depth and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, DeepSeek V3.1 or GLM-5?
GLM-5 supports 200k tokens, while DeepSeek V3.1 supports 64K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, DeepSeek V3.1 or GLM-5?
DeepSeek V3.1 is cheaper on tracked token pricing. DeepSeek V3.1 costs $0.56/1M input and $1.68/1M output tokens. GLM-5 costs $0.72/1M input and $2.3/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3.1 or GLM-5 open source?
DeepSeek V3.1 is listed under Open Source. GLM-5 is listed under MIT. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, DeepSeek V3.1 or GLM-5?
DeepSeek V3.1 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, DeepSeek V3.1 or GLM-5?
DeepSeek V3.1 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run DeepSeek V3.1 and GLM-5?
DeepSeek V3.1 is available on Microsoft Foundry, Fireworks AI, NVIDIA NIM, Together AI, and AWS Bedrock. GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.