Llama 3 70B Instruct vs Xiaomi MiMo-V2.5-Pro
Llama 3 70B Instruct (2024) and Xiaomi MiMo-V2.5-Pro (2026) compare a standalone API model against a coding-specialized model. Llama 3 70B Instruct ships a 8k-token context window, while Xiaomi MiMo-V2.5-Pro ships a 1.05m-token context window. On MMLU PRO, Xiaomi MiMo-V2.5-Pro leads by 11.1 pts. On pricing, Llama 3 70B Instruct costs $0.40/1M input tokens versus $0.43/1M 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: Llama 3 70B Instruct 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 | Llama 3 70B Instruct | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | provider-routed production | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, Classification, and JSON / Tool use | Coding, RAG, and Agents |
| Context window | 8k | 1.05m |
| Cheapest output | $0.40/1M tokens | $0.87/1M tokens |
| Provider routes | 18 tracked | 3 tracked |
| Shared benchmarks | 2 rows | MMLU PRO leader |
Decision tradeoffs
- Llama 3 70B Instruct has the lower cheapest tracked output price at $0.40/1M tokens.
- Llama 3 70B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3 70B Instruct for Coding, Classification, and JSON / Tool use.
- Xiaomi MiMo-V2.5-Pro holds a shared-benchmark lead on MMLU PRO, ahead by 11.1 points.
- Xiaomi MiMo-V2.5-Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Xiaomi MiMo-V2.5-Pro uniquely exposes Function calling and Tool use in local model data.
- 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.
Llama 3 70B Instruct
$420
Cheapest tracked route/tier: Hyperbolic AI Inference
Xiaomi MiMo-V2.5-Pro
$566
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $146. 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 $0.47/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Xiaomi MiMo-V2.5-Pro adds Function calling and Tool use in local capability data.
- Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
- Llama 3 70B Instruct is $0.47/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-18 | 2026-04-22 |
| Context window | 8k | 1.05m |
| Parameters | 70B | 1T |
| Architecture | decoder only | mixture of experts |
| License | Llama 3 Community | Proprietary |
| Openness | Open weights | Proprietary |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Pricing attribute | Llama 3 70B Instruct | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Input price | $0.40/1M tokens | $0.43/1M tokens |
| Output price | $0.40/1M tokens | $0.87/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3 70B Instruct | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 3 70B Instruct | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| MMLU PRO | 57.4 | 68.5 |
| Massive Multitask Language Understanding | 82.0 | 89.4 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 3 70B Instruct at 57.4 and Xiaomi MiMo-V2.5-Pro at 68.5, with Xiaomi MiMo-V2.5-Pro ahead by 11.1 points; Massive Multitask Language Understanding has Llama 3 70B Instruct at 82 and Xiaomi MiMo-V2.5-Pro at 89.4, with Xiaomi MiMo-V2.5-Pro ahead by 7.4 points. The largest visible gap is 11.1 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 function calling: Xiaomi MiMo-V2.5-Pro and tool use: Xiaomi MiMo-V2.5-Pro. 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, Llama 3 70B Instruct lists $0.40/1M input and $0.40/1M 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 Llama 3 70B Instruct lower by about $0.17 per million blended tokens. Availability is 18 providers versus 3, so concentration risk also matters.
Choose Llama 3 70B Instruct when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Xiaomi MiMo-V2.5-Pro when coding workflow support 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, Llama 3 70B Instruct or Xiaomi MiMo-V2.5-Pro?
Xiaomi MiMo-V2.5-Pro supports 1.05m tokens, while Llama 3 70B Instruct supports 8k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Llama 3 70B Instruct or Xiaomi MiMo-V2.5-Pro?
Llama 3 70B Instruct is cheaper on tracked token pricing. Llama 3 70B Instruct costs $0.40/1M input and $0.40/1M 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 Llama 3 70B Instruct or Xiaomi MiMo-V2.5-Pro open source?
Llama 3 70B Instruct is listed under Llama 3 Community. 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 function calling, Llama 3 70B Instruct or Xiaomi MiMo-V2.5-Pro?
Xiaomi MiMo-V2.5-Pro has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, Llama 3 70B Instruct or Xiaomi MiMo-V2.5-Pro?
Xiaomi MiMo-V2.5-Pro has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Llama 3 70B Instruct and Xiaomi MiMo-V2.5-Pro?
Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. 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.
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Last reviewed: 2026-05-26. Data sourced from public model cards and provider documentation.