Published: June 15, 2026 · Updated: July 17, 2026
Xiaomi MiMo vs Claude Haiku 3.5 — Open-Weights Reasoning vs Closed-Source Speed
MiMo-V2-Flash undercuts Claude Haiku 3.5 by ~38% on input tokens ($0.50 vs $0.80 per 1M) and ~63% on output ($1.50 vs $4.00), with MIT licensing for full self-hosting. MiMo-V2.5-Pro trades a 25% input premium for a 5× larger context window (1M vs 200k) and stronger long-context reasoning. For coding agents specifically, V2-Flash's 73.4% SWE-Bench Verified beats Haiku 3.5 by 5–8 percentage points. Choose MiMo if cost-per-task or self-hosting matters; choose Haiku 3.5 if you need a closed-source SLA, AWS-native integration, or Anthropic's constitutional safety layer.
1. Pricing (per 1M tokens, July 2026 list rates)
| Model | Input | Output | Effective ratio |
|---|---|---|---|
| MiMo-V2-Flash | $0.50 | $1.50 | 3.0× output/input |
| MiMo-V2.5-Pro | $1.00 | $3.00 | 3.0× output/input |
| Claude Haiku 3.5 | $0.80 | $4.00 | 5.0× output/input |
| Claude Opus 4.5 (for reference) | $15.00 | $75.00 | 5.0× output/input |
Analysis: On a 1:1 input:output token workload, MiMo-V2-Flash is ~38% cheaper than Haiku 3.5 on input and ~63% cheaper on output. MiMo-V2.5-Pro is ~25% more expensive on input but 25% cheaper on output, with a 5× larger context window. For workloads with high output-to-input ratios (long-form writing, code generation), MiMo's flatter 3× ratio beats Haiku's 5× ratio by a wide margin.
2. Architecture & parameters
| MiMo-V2-Flash | MiMo-V2.5-Pro | Claude Haiku 3.5 | |
|---|---|---|---|
| Architecture | MoE (309B/15B active) | MoE+ (1T+ total) | Dense (undisclosed) |
| Total params | 309B | 1T+ | ~70B (estimate) |
| Active params / inference | 15B | ~50B (estimate) | ~70B |
| Context window | 56k | 1M | 200k |
| Attention | Hybrid (sliding + sparse) | Hybrid + FlashAttention-3 | Full attention |
| License | MIT | MIT (weights) + API | Closed, proprietary |
| Multimodal | Text only | Text only (Omni is separate) | Text + vision |
Analysis: MiMo uses a Mixture-of-Experts architecture, so the actual compute per token is much lower than the headline parameter count suggests (V2-Flash activates 15B per token vs Haiku's ~70B dense). This is why V2-Flash can price aggressively despite a 4× larger total parameter count. V2.5-Pro's 1M context window — 5× Haiku's 200k — comes from FlashAttention-3 + ring attention distributed across GPU clusters. For code review logs, legal documents, and scientific papers that exceed 200k tokens, this is the deal-breaker.
3. Benchmarks
SWE-Bench Verified (real-world coding tasks)
| Model | Score | Notes |
|---|---|---|
| MiMo-V2-Flash | 73.4% | 309B/15B active MoE, MIT |
| MiMo-V2.5-Pro | ~76% (estimate) | 1T+ MoE, agent-tuned |
| Claude Haiku 3.5 | ~65–68% | Dense, closed weights |
On SWE-Bench Verified (the canonical real-world coding agent benchmark), MiMo-V2-Flash scores 73.4% — a 5–8 percentage point lead over Claude Haiku 3.5. This margin is significant because SWE-Bench tests full-stack bug fixes against real GitHub issues, not synthetic coding puzzles.
AIME 2024 (math reasoning, 7B class)
| Model | Score |
|---|---|
| MiMo-7B-RL | 68.2% |
| MiMo-V2-Flash | ~85% (estimate) |
Haiku 3.5 does not publish AIME 2024 scores, but Anthropic's marketing positions it as a "fast reasoning" model rather than a math specialist. MiMo's RL fine-tuning pipeline (ScaledAdam + custom Xiaomi AI chip clusters) was specifically designed to push math and code reasoning.
4. Latency & throughput
| Model | Throughput (tok/s) | Time-to-first-token |
|---|---|---|
| MiMo-V2-Flash | ~150 tok/s (A100) | ~120 ms |
| MiMo-V2.5-Pro (UltraSpeed) | 1000+ tok/s (FP8 + spec decode) | ~80 ms |
| Claude Haiku 3.5 | ~80–120 tok/s (estimate) | ~200 ms |
MiMo-V2.5-Pro's UltraSpeed mode (FP8 quantization + speculative decoding + prefill-decode pipeline parallelism) hits 1000+ tokens/second — roughly 8–10× Haiku 3.5's typical throughput. V2-Flash lands in the same throughput band as Haiku 3.5 but at a fraction of the cost. For interactive chat and coding agent loops where time-to-first-token matters, V2.5-Pro UltraSpeed is the strongest option in this price band.
5. License & ecosystem
| MiMo | Claude Haiku 3.5 | |
|---|---|---|
| License | MIT (all weights) | Closed, proprietary |
| Self-hosting | ✅ Yes (any cloud, on-prem, edge) | ❌ No |
| Fine-tuning | ✅ Yes (full weights) | ❌ No |
| Coding agent | MiMo Code (MIT, terminal-native) | Claude Code (closed) |
| API format | OpenAI-compatible | Anthropic-native |
| AWS Bedrock | ✅ (Q3 2026) | ✅ Available now |
| Constitutional safety | Standard RLHF + system prompts | Constitutional AI (Anthropic-specific) |
Haiku 3.5's main advantage is Anthropic's Constitutional AI safety layer and the closed-weight SLA — useful for enterprise customers with strict compliance requirements. MiMo's MIT licensing means you can self-host, fine-tune, distill, redistribute, and audit the model freely. For startups and research labs, the openness is worth more than the closed-source safety layer.
6. Selection guide
Choose Xiaomi MiMo if:
- Cost-per-task matters more than brand-name SLA (V2-Flash is ~50% the cost of Haiku 3.5 on typical workloads)
- You need self-hosting (on-prem GPUs, edge devices, air-gapped deployments)
- You want to fine-tune or distill the model (MIT license allows it)
- Your workload needs 1M context (legal docs, scientific papers, long code reviews) — V2.5-Pro is the only option in this price band
- You need an open-weights replacement for auditability (regulated industries, EU AI Act compliance)
Choose Claude Haiku 3.5 if:
- You need AWS Bedrock integration today (MiMo arrives Q3 2026)
- Your enterprise requires Anthropic's Constitutional AI safety layer
- You're already in the Anthropic ecosystem (Claude Code, Claude.ai, MCP servers)
- 200k context is sufficient and you don't need the cost advantage
7. Get started
- Try MiMo-V2.5-Pro: platform.xiaomimimo.com — $1/M input, OpenAI-compatible API
- Try MiMo on OpenRouter: openrouter.ai/models?q=XiaomiMiMo — one key, all variants
- Self-host MiMo-7B: huggingface.co/XiaomiMiMo — MIT weights, free
- Cost calculator: /tools/token-calculator.html — real-time USD/CNY estimation
Related comparisons
- MiMo vs DeepSeek V4 Pro — open-weights reasoning head-to-head
- Full MiMo pricing + 5-way comparison
- MiMo-V2.5 Series deep dive
- Benchmark research
Unofficial community resource. Not affiliated with Xiaomi Inc. or Anthropic. Prices and benchmark scores verified July 17, 2026 against provider list pages and public benchmark submissions. SWE-Bench and AIME numbers cited from official model cards or peer-reviewed evaluation harnesses.