GLM-5 vs Xiaomi MiMo-V2.5-Pro
GLM-5 (2026) and Xiaomi MiMo-V2.5-Pro (2026) compare a standalone API model against a coding-specialized model. GLM-5 ships a 200k-token context window, while Xiaomi MiMo-V2.5-Pro ships a 1.05m-token context window. On MMLU PRO, GLM-5 leads by 17.5 pts. On pricing, Xiaomi MiMo-V2.5-Pro costs $0.43/1M input tokens versus $0.60/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: GLM-5 is standalone API model, while Xiaomi MiMo-V2.5-Pro is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | GLM-5 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 200k | 1.05m |
| Cheapest output | $2.08/1M tokens | $0.87/1M tokens |
| Provider routes | 7 tracked | 3 tracked |
| Shared benchmarks | MMLU PRO leader | 4 rows |
Decision tradeoffs
- GLM-5 holds a shared-benchmark lead on MMLU PRO, ahead by 17.5 points.
- GLM-5 has broader tracked provider coverage for fallback and procurement flexibility.
- GLM-5 uniquely exposes Reasoning in local model data.
- Local decision data tags GLM-5 for Coding, RAG, and Agents.
- Xiaomi MiMo-V2.5-Pro holds a shared-benchmark lead on SWE-bench Verified, ahead by 1.1 points.
- Xiaomi MiMo-V2.5-Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Xiaomi MiMo-V2.5-Pro has the lower cheapest tracked output price at $0.87/1M tokens.
- Local decision data tags Xiaomi MiMo-V2.5-Pro for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GLM-5
$1,000
Cheapest tracked route/tier: OpenRouter
Xiaomi MiMo-V2.5-Pro
$566
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $435. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
- Xiaomi MiMo-V2.5-Pro is $1.21/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning before moving production traffic.
- Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
- GLM-5 is $1.21/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GLM-5 adds Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-11 | 2026-04-22 |
| Context window | 200k | 1.05m |
| Parameters | 744B total, 40B active | 1T |
| Architecture | mixture of experts | mixture of experts |
| License | MIT(OSI) | Proprietary |
| Openness | Open source | Proprietary |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | 2025-11 | - |
Pricing and availability
| Pricing attribute | GLM-5 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Input price | $0.60/1M tokens | $0.43/1M tokens |
| Output price | $2.08/1M tokens | $0.87/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GLM-5 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| MMLU PRO | 86.0 | 68.5 |
| SWE-bench Verified | 77.8 | 78.9 |
| SWE-bench Pro | 55.1 | 57.2 |
| Google-Proof Q&A | 86.0 | 66.7 |
Deep dive
On shared benchmark coverage, MMLU PRO has GLM-5 at 86 and Xiaomi MiMo-V2.5-Pro at 68.5, with GLM-5 ahead by 17.5 points; SWE-bench Verified has GLM-5 at 77.8 and Xiaomi MiMo-V2.5-Pro at 78.9, with Xiaomi MiMo-V2.5-Pro ahead by 1.1 points; SWE-bench Pro has GLM-5 at 55.1 and Xiaomi MiMo-V2.5-Pro at 57.2, with Xiaomi MiMo-V2.5-Pro ahead by 2.1 points. The largest visible gap is 17.5 points on MMLU PRO, 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 reasoning mode: GLM-5. Both models share function calling, tool use, 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, GLM-5 lists $0.60/1M input and $2.08/1M output tokens on the cheapest tracked provider, while Xiaomi MiMo-V2.5-Pro lists $0.43/1M input and $0.87/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Xiaomi MiMo-V2.5-Pro lower by about $0.48 per million blended tokens. Availability is 7 providers versus 3, so concentration risk also matters.
Choose GLM-5 when reasoning depth and broader provider choice are central to the workload. Choose Xiaomi MiMo-V2.5-Pro when coding workflow support, larger context windows, and lower input-token cost 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, GLM-5 or Xiaomi MiMo-V2.5-Pro?
Xiaomi MiMo-V2.5-Pro supports 1.05m tokens, while GLM-5 supports 200k 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, GLM-5 or Xiaomi MiMo-V2.5-Pro?
Xiaomi MiMo-V2.5-Pro is cheaper on tracked token pricing. GLM-5 costs $0.60/1M input and $2.08/1M output tokens. Xiaomi MiMo-V2.5-Pro costs $0.43/1M input and $0.87/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5 or Xiaomi MiMo-V2.5-Pro open source?
GLM-5 is listed under MIT. Xiaomi MiMo-V2.5-Pro is listed under Proprietary. 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 reasoning mode, GLM-5 or Xiaomi MiMo-V2.5-Pro?
GLM-5 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, GLM-5 or Xiaomi MiMo-V2.5-Pro?
Both GLM-5 and Xiaomi MiMo-V2.5-Pro expose function calling. 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 GLM-5 and Xiaomi MiMo-V2.5-Pro?
GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. Xiaomi MiMo-V2.5-Pro is available on OpenRouter, Xiaomi, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-26. Data sourced from public model cards and provider documentation.