Pick Grok 4.7 for 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price or deepswe v1.1 (high effort): 71.0%, up from grok 4.6's 65.2%; cursorbench 4.0: 46.3%, up from 40.4%. Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). Choose MiMo-V2.5 if you need self-hosting or data privacy; Grok 4.7 if you want a managed API.
Grok 4.7 (xAI, US) and MiMo-V2.5 (Xiaomi, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Grok 4.7 is xAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: MiMo-V2.5 is about 14× cheaper on input ($0.14/$0.28 per 1M tokens vs $2/$6 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: MiMo-V2.5 holds 2× more — 1M (~1,500 pages) vs 500K tokens (~750 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Grok 4.7 is the newer model by about 5 months (released September 21, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Grok 4.7
MiMo-V2.5
Provider
xAI (US)
Xiaomi (China)
Released
September 21, 2026
April 22, 2026
Context window
500K tokens (~750 pages)
1M (~1,500 pages)
Price (in/out)
$2/$6 per 1M tokens
$0.14/$0.28 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, image, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
2.1 trillion parameters, up 40% from Grok 4.6's 1.5 trillion, at the same $2/$6 per million token price: Grok 4.7 — XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks — and it is the newer of the two.
DeepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4%: Grok 4.7 — Grok 4.7 lists deepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4% among its strengths; MiMo-V2.5 does not.
Trained with supplemental SpaceX data (Starlink telemetry, manufacturing records, engineering failure logs) — xAI says this improves reasoning about hardware and physical systems: Grok 4.7 — MiMo-V2.5 is comparatively weak here — not the deepest reasoning tier (see V2.5-Pro)
Native omnimodal — strong image and video understanding: MiMo-V2.5 — Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and it runs cheaper at $0.14/$0.28 per 1M tokens.
Very low cost (~half the inference of the Pro tier): MiMo-V2.5 — At $0.14/$0.28 per 1M tokens it undercuts Grok 4.7 ($2/$6 per 1M tokens), and that gap compounds at volume.
Agent-framework integration: MiMo-V2.5 — Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and it carries the larger 1M context.
Lowest cost at scale: MiMo-V2.5 — At $0.14/$0.28 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: MiMo-V2.5 — Its 1M window is about 2× larger than Grok 4.7's 500K tokens, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MiMo-V2.5 — At $0.14/$0.28 per 1M tokens it undercuts Grok 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: MiMo-V2.5 — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: MiMo-V2.5 — Open weights let you run it on your own hardware; Grok 4.7 is API-only.
Anyone whose priority is 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price: Grok 4.7 — It is specifically built for that.
Anyone whose priority is native omnimodal — strong image and video understanding: MiMo-V2.5 — That is its strongest area.
An enterprise with regional data-residency rules: Grok 4.7 or MiMo-V2.5 — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Grok 4.7: where it fits
XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks. Released September 21, 2026 by xAI, it is built for 2.1 trillion parameters, up 40% from Grok 4.6's 1.5 trillion, at the same $2/$6 per million token price, deepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4%, trained with supplemental SpaceX data (Starlink telemetry, manufacturing records, engineering failure logs) — xAI says this improves reasoning about hardware and physical systems, and xAI's strongest safety guardrails to date, per the company.
Its trade-offs are real: release was delayed at least five times since late July 2026 before shipping, 500K context window trails several rivals now sitting at 1M+, and reviewers note it arrives "late to the AI frontier party" against GPT-6 Astra, Claude Fable 5.1 and Opus 5.5, all shipped in the weeks just before it. At $2 in / $6 out per million tokens, it sits in the mid price band.
MiMo-V2.5: where it fits
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Released April 22, 2026 by Xiaomi, it is built for native omnimodal — strong image and video understanding, very low cost (~half the inference of the Pro tier), agent-framework integration, and 1M context for full documents in one pass.
Its trade-offs: not the deepest reasoning tier (see V2.5-Pro), and limited Western tooling and support. At $0.14 in / $0.28 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. MiMo-V2.5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Grok 4.7 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is Grok 4.7 or MiMo-V2.5 better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Grok 4.7 leans toward 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price while MiMo-V2.5 leans toward native omnimodal — strong image and video understanding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Grok 4.7 or MiMo-V2.5?
MiMo-V2.5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Grok 4.7 is API-metered at $2/$6 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
MiMo-V2.5 — 1M vs 500K tokens, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4.7 and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you Grok 4.7, MiMo-V2.5 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Grok 4.7 or MiMo-V2.5?
Grok 4.7 — released September 21, 2026, about 5 months after MiMo-V2.5.
Grok 4.7 vs MiMo-V2.5
xAI · US | Xiaomi · China · Updated June 2026
Quick verdict
Pick Grok 4.7 for 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price or deepswe v1.1 (high effort): 71.0%, up from grok 4.6's 65.2%; cursorbench 4.0: 46.3%, up from 40.4%. Pick MiMo-V2.5 for native omnimodal — strong image and video understanding or very low cost (~half the inference of the pro tier). Choose MiMo-V2.5 if you need self-hosting or data privacy; Grok 4.7 if you want a managed API.
Grok 4.7 (xAI, US) and MiMo-V2.5 (Xiaomi, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Grok 4.7 is xAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks. MiMo-V2.5 is xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: MiMo-V2.5 is about 14× cheaper on input ($0.14/$0.28 per 1M tokens vs $2/$6 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: MiMo-V2.5 holds 2× more — 1M (~1,500 pages) vs 500K tokens (~750 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Grok 4.7 is the newer model by about 5 months (released September 21, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Grok 4.7
MiMo-V2.5
Provider
xAI (US)
Xiaomi (China)
Released
September 21, 2026
April 22, 2026
Context window
500K tokens (~750 pages)
1M (~1,500 pages)
Price (in/out)
$2/$6 per 1M tokens
$0.14/$0.28 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, image, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
2.1 trillion parameters, up 40% from Grok 4.6's 1.5 trillion, at the same $2/$6 per million token price
Grok 4.7
XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks — and it is the newer of the two.
DeepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4%
Grok 4.7
Grok 4.7 lists deepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4% among its strengths; MiMo-V2.5 does not.
Trained with supplemental SpaceX data (Starlink telemetry, manufacturing records, engineering failure logs) — xAI says this improves reasoning about hardware and physical systems
Grok 4.7
MiMo-V2.5 is comparatively weak here — not the deepest reasoning tier (see V2.5-Pro)
Native omnimodal — strong image and video understanding
MiMo-V2.5
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and it runs cheaper at $0.14/$0.28 per 1M tokens.
Very low cost (~half the inference of the Pro tier)
MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts Grok 4.7 ($2/$6 per 1M tokens), and that gap compounds at volume.
Agent-framework integration
MiMo-V2.5
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost — and it carries the larger 1M context.
Lowest cost at scale
MiMo-V2.5
At $0.14/$0.28 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
MiMo-V2.5
Its 1M window is about 2× larger than Grok 4.7's 500K tokens, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MiMo-V2.5
At $0.14/$0.28 per 1M tokens it undercuts Grok 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ MiMo-V2.5
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ MiMo-V2.5
Open weights let you run it on your own hardware; Grok 4.7 is API-only.
Anyone whose priority is 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price
→ Grok 4.7
It is specifically built for that.
Anyone whose priority is native omnimodal — strong image and video understanding
→ MiMo-V2.5
That is its strongest area.
An enterprise with regional data-residency rules
→ Grok 4.7 or MiMo-V2.5
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Grok 4.7: where it fits
XAI's September 21, 2026 update — a 2.1T-parameter model trained partly on SpaceX hardware data, same price as Grok 4.6 but stronger on coding benchmarks. Released September 21, 2026 by xAI, it is built for 2.1 trillion parameters, up 40% from Grok 4.6's 1.5 trillion, at the same $2/$6 per million token price, deepSWE v1.1 (high effort): 71.0%, up from Grok 4.6's 65.2%; CursorBench 4.0: 46.3%, up from 40.4%, trained with supplemental SpaceX data (Starlink telemetry, manufacturing records, engineering failure logs) — xAI says this improves reasoning about hardware and physical systems, and xAI's strongest safety guardrails to date, per the company.
Its trade-offs are real: release was delayed at least five times since late July 2026 before shipping, 500K context window trails several rivals now sitting at 1M+, and reviewers note it arrives "late to the AI frontier party" against GPT-6 Astra, Claude Fable 5.1 and Opus 5.5, all shipped in the weeks just before it. At $2 in / $6 out per million tokens, it sits in the mid price band.
MiMo-V2.5: where it fits
Xiaomi's cheap omnimodal model — Pro-level agentic perception across image and video at a fraction of the cost. Released April 22, 2026 by Xiaomi, it is built for native omnimodal — strong image and video understanding, very low cost (~half the inference of the Pro tier), agent-framework integration, and 1M context for full documents in one pass.
Its trade-offs: not the deepest reasoning tier (see V2.5-Pro), and limited Western tooling and support. At $0.14 in / $0.28 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. MiMo-V2.5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Grok 4.7 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both Grok 4.7 and MiMo-V2.5 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Grok 4.7 leans toward 2.1 trillion parameters, up 40% from grok 4.6's 1.5 trillion, at the same $2/$6 per million token price while MiMo-V2.5 leans toward native omnimodal — strong image and video understanding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Grok 4.7 or MiMo-V2.5?
MiMo-V2.5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Grok 4.7 is API-metered at $2/$6 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
MiMo-V2.5 — 1M vs 500K tokens, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Grok 4.7 and MiMo-V2.5 together?
Yes — a multi-model platform like LumiChats gives you Grok 4.7, MiMo-V2.5 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Grok 4.7 or MiMo-V2.5?
Grok 4.7 — released September 21, 2026, about 5 months after MiMo-V2.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.