DeepSeek V3.1 vs GLM-5V-Turbo
DeepSeek V3.1 (2025) and GLM-5V-Turbo (2026) are frontier reasoning models from DeepSeek and Zhipu AI. DeepSeek V3.1 ships a 64k-token context window, while GLM-5V-Turbo ships a 200k-token context window. On pricing, DeepSeek V3.1 costs $0.27/1M input tokens versus $1.20/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
DeepSeek V3.1 is ~344% cheaper at $0.27/1M; pay for GLM-5V-Turbo only for reasoning depth.
Decision scorecard
Local evidence first| Signal | DeepSeek V3.1 | GLM-5V-Turbo |
|---|---|---|
| Best for | multimodal apps and provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, Agents, and Vision | RAG, Agents, and Long context |
| Context window | 64k | 200k |
| Cheapest output | $1/1M tokens | $4/1M tokens |
| Provider routes | 8 tracked | 2 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- DeepSeek V3.1 has the lower cheapest tracked output price at $1/1M tokens.
- DeepSeek V3.1 has broader tracked provider coverage for fallback and procurement flexibility.
- DeepSeek V3.1 uniquely exposes Code execution in local model data.
- Local decision data tags DeepSeek V3.1 for Coding, Agents, and Vision.
- GLM-5V-Turbo has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5V-Turbo uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags GLM-5V-Turbo for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek V3.1
$466
Cheapest tracked route/tier: Novita AI
GLM-5V-Turbo
$1,960
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $1,494. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- GLM-5V-Turbo is $3/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Code execution before moving production traffic.
- GLM-5V-Turbo adds Reasoning, Function calling, and Tool use in local capability data.
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- DeepSeek V3.1 is $3/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- DeepSeek V3.1 adds Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-21 | 2026-04-01 |
| Context window | 64k | 200k |
| Parameters | 671B total, 37B active (MoE) | 744B total, 40B active |
| Architecture | mixture of experts | mixture of experts |
| License | MIT(OSI) | MIT(OSI) |
| Openness | Open source | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | - | 2025-11 |
Pricing and availability
| Pricing attribute | DeepSeek V3.1 | GLM-5V-Turbo |
|---|---|---|
| Input price | $0.27/1M tokens | $1.20/1M tokens |
| Output price | $1/1M tokens | $4/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3.1 | GLM-5V-Turbo |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: GLM-5V-Turbo, function calling: GLM-5V-Turbo, tool use: GLM-5V-Turbo, and code execution: DeepSeek V3.1. Both models share vision, multimodal input, and 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 $0.27/1M input and $1/1M output tokens on the cheapest tracked provider, while GLM-5V-Turbo lists $1.20/1M input and $4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3.1 lower by about $1.55 per million blended tokens. Availability is 8 providers versus 2, 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-5V-Turbo 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, DeepSeek V3.1 or GLM-5V-Turbo?
GLM-5V-Turbo 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-5V-Turbo?
DeepSeek V3.1 is cheaper on tracked token pricing. DeepSeek V3.1 costs $0.27/1M input and $1/1M output tokens. GLM-5V-Turbo costs $1.20/1M input and $4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3.1 or GLM-5V-Turbo open source?
DeepSeek V3.1 is listed under MIT. GLM-5V-Turbo 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-5V-Turbo?
Both DeepSeek V3.1 and GLM-5V-Turbo expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. 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-5V-Turbo?
Both DeepSeek V3.1 and GLM-5V-Turbo expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run DeepSeek V3.1 and GLM-5V-Turbo?
DeepSeek V3.1 is available on Microsoft Foundry, Fireworks AI, NVIDIA NIM, Together AI, and AWS Bedrock. GLM-5V-Turbo is available on OpenRouter and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.