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Xiaomi MiMo V2.5

V2.5

Ship the V2.5 series in public beta — Xiaomi positions V2.5-Pro to go head-to-head with Claude Opus 4.6 and GPT-5.4 on long-horizon agentic work, staying stable across ~1,000 tool calls in a single 1M-token session Run native omnimodal V2.5 across image, audio, and video understanding at 1M context — surpasses V2-Pro on Claw-Eval while cutting API cost roughly 50% and saving 50% tokens vs Muse Spark at the same score Access V2.5-Pro from $1/M input and $3/M output (≤256K) or $2/$6 for 256K–1M, with V2.5 at $0.40/$2 input/output, V2.5-TTS free during beta, and open-source weights planned for V2.5 and V2.5-Pro

Reviewed by ToolWorthy Editors·updated 1 month ago

Pricing:Free + from $0.40/per 1M input tokens (V2.5 ≤256K)
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Pros & Cons

Pros

  • V2.5-Pro matches V2-Pro pricing at a higher capability tier — effectively a free upgrade for existing V2-Pro API users
  • Omnimodal V2.5 at $0.40/M input beats the previous V2-Pro benchmark scores at roughly half the cost
  • Demonstrated multi-hour, thousand-tool-call agent runs give concrete evidence for long-horizon workloads instead of leaderboard-only claims
  • Drop-in OpenAI / Anthropic API compatibility means migration from Claude Opus 4.6 or GPT-5 stacks rarely requires SDK changes
  • Token efficiency (42% vs Kimi K2.6, 50% vs Muse Spark at matched scores) compounds savings beyond headline per-token pricing

Cons

  • Public beta status means SLAs, uptime guarantees, and long-term pricing stability are not yet committed
  • Multimodal benchmark claims (VideoMME, CharXiv, MMMU-Pro) are directional — exact numbers have not been published for V2.5
  • Open-source weights for V2.5 and V2.5-Pro are announced but not yet released; API-only access at launch
  • Long-horizon evidence relies on two internal tasks rather than a broader independent benchmark suite
  • Rate limits of 100 RPM / 10M TPM are shared across all API keys per account, which can constrain team-scale deployments

Overview

Xiaomi MiMo V2.5 entered public beta on April 23, 2026 — a new V2.5 model family led by MiMo-V2.5 and MiMo-V2.5-Pro on the text/omnimodal side, with V2.5-TTS Series and V2.5-ASR announced alongside. It replaces the one-flagship setup from the V2-Pro release just five weeks earlier. The redesign pushes on two axes at once: V2.5-Pro targets very long agentic runs where Claude Opus 4.6 and GPT-5.4 currently lead, while the non-Pro V2.5 folds what used to be the separate V2-Omni multimodal model into the main text reasoning model and drops it to roughly half the price.

The launch also swaps the Token Plan credit scheme, removes the 256K/1M tier penalty, and comes with a full Credits reset for existing subscribers before 22:00 CST on April 22, 2026.

What's New

MiMo-V2.5-Pro: Longer-Horizon Agents

Xiaomi positions V2.5-Pro explicitly against Claude Opus 4.6 and GPT-5.4 for long-horizon agentic work rather than single-turn benchmarks — framing it as able to "go head-to-head" on agentic scenarios rather than citing third-party consensus. Xiaomi reports stable execution across roughly 1,000 tool calls in a single session within a 1M-token context window, with maximum output extended to 128K tokens. Two long-running tasks were disclosed as evidence rather than leaderboard scores:

  • Rust SysY compiler (Peking University compiler-principles project). V2.5-Pro wrote a full compiler pipeline — lexer, parser, AST, Koopa IR codegen, RISC-V assembly backend, and performance optimization — in 4.3 hours across 672 tool calls. Hidden test score: 233/233, with perfect sub-scores on Koopa IR (110/110), RISC-V backend (103/103), and optimization (20/20). Cold-start compile pass rate was 59% (137/233) on the first build, meaning the architecture was correct before the test harness ever ran.
  • Video editor web app. From the prompt "build a video editor web app," V2.5-Pro produced a working 8,192-line application with multi-track timeline, clip trimming, crossfade, audio mixing, and export — across 1,868 tool calls over 11.5 hours of autonomous work.

Instruction-following in long agent sessions was also specifically called out — V2.5-Pro is described as picking up implicit requirements from earlier context and staying logically consistent across very long runs, which is where AI agent frameworks typically break down in production.

MiMo-V2.5: Native Omnimodal at 1M Context

The non-Pro V2.5 is a native omnimodal model that handles image, audio, and video input in the same reasoning loop rather than routing through a separate vision or speech pipeline. Two claims frame the upgrade:

  • Agent capability surpasses MiMo-V2-Pro on Claw-Eval — meaning the cheaper, omnimodal sibling now beats the previous flagship on Xiaomi's primary agent benchmark, while cutting API cost by roughly 50% at matched throughput.
  • Multimodal perception surpasses MiMo-V2-Omni on VideoMME, CharXiv, and MMMU-Pro, approaching or exceeding top closed-source models on those evaluations.

Context window is 1M tokens with 128K max output — matching V2.5-Pro on capacity but at a lower price tier. V2.5 is positioned for the "everyday" Agent scenarios where V2.5-Pro's long-horizon reliability is overkill.

Token-Efficiency Gains Across the Family

At matched ClawEval scores, Xiaomi measures:

  • V2.5-Pro saves 42% tokens vs Kimi K2.6 at the same agent benchmark score.
  • V2.5 saves 50% tokens vs Muse Spark at the same agent benchmark score.

This matters because agent billing scales with tool-call verbosity as much as with per-million-token rates — a 40-50% reduction in tokens consumed can outweigh headline input/output price comparisons for multi-turn workloads.

Four-Model Family + Token Plan Reset

Alongside the two LLMs, V2.5-TTS Series covers three speech-synthesis variants (base, voice-clone, voice-design) and V2.5-ASR handles speech recognition. Xiaomi's pricing page currently lists all TTS/ASR variants as free during the beta window, though individual endpoints may roll out after the core V2.5 / V2.5-Pro launch. Token Plan credit rates flattened to V2.5 = 1×, V2.5-Pro = 2× with the 256K/1M credit multiplier removed; overnight (00:00–08:00 CST) calls get an additional 20% off; new annual plans come in at 88% of list price.

Performance Benchmarks

The two long-horizon evidence items are worth restating because they describe a capability profile not captured by standard single-turn evals.

Task Duration Tool Calls Outcome
Peking University SysY compiler in Rust 4.3 hours 672 233/233 on hidden tests (Koopa IR 110/110, RISC-V 103/103, perf 20/20); 59% cold-start compile pass rate
"Build a video editor web app" 11.5 hours 1,868 8,192 lines of working code; multi-track timeline, crossfade, audio mixing, export

For MiMo-V2.5 on the omnimodal side, Xiaomi cites gains on VideoMME, CharXiv, and MMMU-Pro over MiMo-V2-Omni but has not yet published the exact numbers — treat those as directional until the official model card lands.

The agent-benchmark claim "V2.5 surpasses V2-Pro on Claw-Eval" is the most load-bearing comparison in the release, since it supports the pricing delta: the cheaper model is being marketed as strictly better on the metric Xiaomi cares about.

Availability & Access

V2.5 launched as a public beta rather than a general-availability release, which shapes how access works today:

Access Path Details
platform.xiaomimimo.com API key issuance + console + usage dashboard
Xiaomi AI Studio Free interactive testing without billing setup
OpenAI / Anthropic API protocols Drop-in compatibility at the SDK level
IDE integrations OpenCode, Claude Code, Cline, Kilo Code, Roo Code, Codex, Cherry Studio, Zed, Qwen Code, OpenClaw
Open-source weights Xiaomi says MiMo-V2.5-Pro and MiMo-V2.5 will be open-sourced "soon"; release venue and timing have not been specified at launch

Rate limiting is shared across all API keys on a single account: 100 RPM and 10M TPM per model. Cache-write pricing is free during the beta window, and network-search plugins bill separately ($5 per 1,000 calls overseas).

Pricing & Plans

V2.5 uses per-token API pricing; Token Plan subscriptions are optional. All overseas rates are per 1M tokens.

Model Tier Input Cached Input Output
V2.5-Pro ≤256K tokens $1.00 $0.20 $3.00
V2.5-Pro 256K–1M tokens $2.00 $0.40 $6.00
V2.5 (omnimodal) ≤256K tokens $0.40 $0.08 $2.00
V2.5 (omnimodal) 256K–1M tokens $0.80 $0.16 $4.00
V2.5-TTS / voiceclone / voicedesign Free (beta)
V2.5-ASR Free (beta)

V2.5-Pro pricing matches V2-Pro at both tiers — new flagship, same cost. V2.5 comes in at 40% of V2.5-Pro's input rate and 67% of its output rate, so the practical decision is "use V2.5 unless the job explicitly needs V2.5-Pro's long-horizon reliability."

For Token Plan subscribers, the key changes vs the V2-Pro-era scheme are:

  • Credit cost now flat at 1× (V2.5) / 2× (V2.5-Pro) — the old 4× Credits multiplier on the 256K–1M tier is gone.
  • Overnight window (00:00–08:00 CST) applies an additional 20% discount on Credits consumed.
  • Auto-renewal adds 30% off next month for existing users (23% for new users), each limited to one use; annual plans land at 88% of list.
  • All Credits balances purchased before 22:00 CST on April 22, 2026 were reset, but subscription time remaining was preserved.

Best For

  • Engineering teams running agent pipelines that exceed 100 tool calls per session and hit reliability walls on shorter-context models
  • Teams migrating off Claude Opus 4.6 or Claude Sonnet 4.6 where long-context work dominates the bill
  • Developers who want an omnimodal model with 1M context at a sub-dollar input rate — a pricing tier Kimi, GLM-5, and Western frontier models currently don't match
  • Token Plan subscribers who benefit from the new flat credit scheme plus overnight and annual discounts
  • Researchers evaluating Chinese frontier LLM progress alongside GLM-5 and Kimi K2.x series at comparable capability tiers

FAQ

Is MiMo V2.5 a replacement for MiMo-V2-Pro?

Practically yes, but the upgrade path depends on workload. V2.5-Pro supersedes V2-Pro on long-horizon agent reliability at identical pricing. For workloads that previously ran on V2-Pro for general capability, the non-Pro V2.5 is a cheaper option and is claimed to beat V2-Pro on Claw-Eval while cutting API cost by roughly half.

How does V2.5-Pro compare to Claude Opus 4.6 and GPT-5.4?

Xiaomi positions V2.5-Pro as able to "go head-to-head" with those models on general agentic ability, complex software engineering, and long-horizon tasks — specifically highlighting ~1,000-tool-call stability and the two demonstrated multi-hour tasks. Independent third-party benchmarks have not yet been published, so treat the positioning as vendor-stated until external evaluations arrive.

What is the difference between MiMo-V2.5 and MiMo-V2-Omni?

MiMo-V2.5 replaces V2-Omni as the omnimodal line. It extends the context window from V2-Omni's 256K to 1M tokens, adds the 256K–1M tier pricing, and claims gains over V2-Omni on VideoMME, CharXiv, and MMMU-Pro — while also surpassing V2-Pro on Claw-Eval, which V2-Omni did not.

Are V2.5 and V2.5-Pro open source?

Not yet. Xiaomi has announced open-source weight releases for both V2.5 and V2.5-Pro but has not published them — or committed to a specific venue or timing — at launch. Earlier MiMo releases (V1 / MiMo-7B and V2-Flash) are open-weight under the XiaomiMiMo organization on Hugging Face and GitHub, but V2.5/V2.5-Pro destinations have not been confirmed.

What changed in the Token Plan at the V2.5 launch?

Three things: the 256K–1M Credit multiplier was removed (all tiers now cost 1× for V2.5 or 2× for V2.5-Pro per token), overnight calls 00:00–08:00 CST get an extra 20% discount, and annual/auto-renewal plans add 12–30% off. All existing Credits balances were reset to zero at 22:00 CST on April 22, 2026, without affecting subscription duration.

Version History

V2.5

Current Version

Released on April 23, 2026

+What's new
3 updates
  • Ship the V2.5 series in public beta — Xiaomi positions V2.5-Pro to go head-to-head with Claude Opus 4.6 and GPT-5.4 on long-horizon agentic work, staying stable across ~1,000 tool calls in a single 1M-token session
  • Run native omnimodal V2.5 across image, audio, and video understanding at 1M context — surpasses V2-Pro on Claw-Eval while cutting API cost roughly 50% and saving 50% tokens vs Muse Spark at the same score
  • Access V2.5-Pro from $1/M input and $3/M output (≤256K) or $2/$6 for 256K–1M, with V2.5 at $0.40/$2 input/output, V2.5-TTS free during beta, and open-source weights planned for V2.5 and V2.5-Pro

V2-Pro

Released on March 18, 2026

View Update
+What's new
3 updates
  • Deploy over 1 trillion parameters with 42B active, a 7:1 hybrid attention ratio, and a 1M-token context window built for production agentic workloads and complex system orchestration
  • Reach 78.0 on SWE-Bench Verified, 61.5 on ClawEval, and 81.0 on PinchBench — ranking 8th globally on the Artificial Analysis Intelligence Index at $1/M input tokens (up to 256K)
  • Access via Xiaomi's AI Studio for interactive testing or the API platform at tiered pricing: $1/M input for up to 256K tokens, $2/M for 256K–1M token prompts

V2-Flash

Released on December 16, 2025

+What's new
3 updates
  • Run a 309B MoE model with 15B active parameters using a 5:1 hybrid attention architecture and Multi-Token Prediction layer for high-speed reasoning and agentic task execution
  • Handle complex reasoning and coding workflows with open-source weights published on Hugging Face and GitHub for self-hosted deployment via vLLM
  • Access the first MiMo model to combine extended thinking, fast token generation, and a dedicated agentic design in a fully open-weight release

V1 (MiMo-7B)

Released on May 7, 2025

+What's new
3 updates
  • Unlock strong reasoning in a compact 7B-parameter model trained from scratch using a reasoning-focused pretraining and posttraining pipeline that surpasses DeepSeek-R1 on AIME24
  • Release fully open-source weights including base model, SFT checkpoint, and RL-trained variants on Hugging Face and GitHub under the XiaomiMiMo organization
  • Demonstrate cost-efficient reinforcement learning for reasoning: MiMo-7B-RL achieves top-tier math and coding performance with a training approach designed for reproducibility

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