Pick Kimi K3 for largest open-weight model at release — 2.8t sparse moe, self-hostable or 1m-token context with native vision (text, image and video). Pick Mistral Medium 3 for strong cost-to-capability at $0.40/$2.00 or general reasoning, coding and multimodal tasks. Choose Kimi K3 if you need self-hosting or data privacy; Mistral Medium 3 if you want a managed API.
Kimi K3 (Moonshot AI, China) and Mistral Medium 3 (Mistral AI, France) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Kimi K3 is moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. Mistral Medium 3 is mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: Mistral Medium 3 is about 7.5× cheaper on input ($0.4/$2 per 1M tokens vs $3/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Kimi K3 holds 8.2× more — 1M (~1,573 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Kimi K3 is the newer model by about 15 months (released July 27, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a China-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Kimi K3
Mistral Medium 3
Provider
Moonshot AI (China)
Mistral AI (France)
Released
July 27, 2026
May 7, 2025
Context window
1M (~1,573 pages)
128K (~192 pages)
Price (in/out)
$3/$15 per 1M tokens
$0.4/$2 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, image, video, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Largest open-weight model at release — 2.8T sparse MoE, self-hostable: Kimi K3 — Open weights make this possible at all — Mistral Medium 3 is API-only, so it cannot leave the vendor's servers.
1M-token context with native vision (text, image and video): Kimi K3 — Its 1M window holds about 8.2× more than Mistral Medium 3's 128K in a single prompt.
Vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness: Kimi K3 — Mistral Medium 3 is comparatively weak here — no published SWE-Bench Verified score
Strong cost-to-capability at $0.40/$2.00: Mistral Medium 3 — At $0.4/$2 per 1M tokens it undercuts Kimi K3 ($3/$15 per 1M tokens), and that gap compounds at volume.
General reasoning, coding and multimodal tasks: Mistral Medium 3 — Kimi K3 is comparatively weak here — coding scores use Moonshot FrontierSWE, not standard SWE-Bench Verified
Efficient mid-tier deployment for production workloads: Mistral Medium 3 — Kimi K3 is comparatively weak here — no independent benchmark reproduction yet at release
Lowest cost at scale: Mistral Medium 3 — At $0.4/$2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Kimi K3 — Its 1M window is about 8.2× larger than Mistral Medium 3's 128K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Mistral Medium 3 — At $0.4/$2 per 1M tokens it undercuts Kimi K3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Kimi K3 — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: Kimi K3 — Open weights let you run it on your own hardware; Mistral Medium 3 is API-only.
Anyone whose priority is largest open-weight model at release — 2.8t sparse moe, self-hostable: Kimi K3 — It is specifically built for that.
Anyone whose priority is strong cost-to-capability at $0.40/$2.00: Mistral Medium 3 — That is its strongest area.
An enterprise with regional data-residency rules: Mistral Medium 3 or Kimi K3 — Origin (China vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Kimi K3: where it fits
Moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. Released July 27, 2026 by Moonshot AI, it is built for largest open-weight model at release — 2.8T sparse MoE, self-hostable, 1M-token context with native vision (text, image and video), vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness, and fresh-input pricing of $3/M (cached $0.30/M), flat across the full 1M context.
Its trade-offs are real: coding scores use Moonshot FrontierSWE, not standard SWE-Bench Verified, 2.8T params need serious hardware to self-host — weights are free, running is not, no independent benchmark reproduction yet at release, and image input but no audio or video. At $3 in / $15 out per million tokens, it sits in the mid price band.
Mistral Medium 3: where it fits
Mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. Released May 7, 2025 by Mistral AI, it is built for strong cost-to-capability at $0.40/$2.00, general reasoning, coding and multimodal tasks, efficient mid-tier deployment for production workloads, and text and image input.
Its trade-offs: a 128K context — smaller than the 1M-window flagships here, no published SWE-Bench Verified score, a mid-tier model, not a frontier reasoner, and proprietary, unlike Mistral's open-weight releases. At $0.4 in / $2 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. Kimi K3 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Mistral Medium 3 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 Kimi K3 or Mistral Medium 3 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, Kimi K3 leans toward largest open-weight model at release — 2.8t sparse moe, self-hostable while Mistral Medium 3 leans toward strong cost-to-capability at $0.40/$2.00, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Kimi K3 or Mistral Medium 3?
Kimi K3 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Mistral Medium 3 is API-metered at $0.4/$2 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?
Kimi K3 — 1M vs 128K, about 8.2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Kimi K3 and Mistral Medium 3 together?
Yes — a multi-model platform like LumiChats gives you Kimi K3, Mistral Medium 3 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, Kimi K3 or Mistral Medium 3?
Kimi K3 — released July 27, 2026, about 15 months after Mistral Medium 3.
Kimi K3 vs Mistral Medium 3
Moonshot AI · China | Mistral AI · France · Updated June 2026
Quick verdict
Pick Kimi K3 for largest open-weight model at release — 2.8t sparse moe, self-hostable or 1m-token context with native vision (text, image and video). Pick Mistral Medium 3 for strong cost-to-capability at $0.40/$2.00 or general reasoning, coding and multimodal tasks. Choose Kimi K3 if you need self-hosting or data privacy; Mistral Medium 3 if you want a managed API.
Kimi K3 (Moonshot AI, China) and Mistral Medium 3 (Mistral AI, France) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Kimi K3 is moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. Mistral Medium 3 is mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. 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: Mistral Medium 3 is about 7.5× cheaper on input ($0.4/$2 per 1M tokens vs $3/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Kimi K3 holds 8.2× more — 1M (~1,573 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Kimi K3 is the newer model by about 15 months (released July 27, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a China-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Kimi K3
Mistral Medium 3
Provider
Moonshot AI (China)
Mistral AI (France)
Released
July 27, 2026
May 7, 2025
Context window
1M (~1,573 pages)
128K (~192 pages)
Price (in/out)
$3/$15 per 1M tokens
$0.4/$2 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, image, video, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Largest open-weight model at release — 2.8T sparse MoE, self-hostable
Kimi K3
Open weights make this possible at all — Mistral Medium 3 is API-only, so it cannot leave the vendor's servers.
1M-token context with native vision (text, image and video)
Kimi K3
Its 1M window holds about 8.2× more than Mistral Medium 3's 128K in a single prompt.
Vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness
Kimi K3
Mistral Medium 3 is comparatively weak here — no published SWE-Bench Verified score
Strong cost-to-capability at $0.40/$2.00
Mistral Medium 3
At $0.4/$2 per 1M tokens it undercuts Kimi K3 ($3/$15 per 1M tokens), and that gap compounds at volume.
General reasoning, coding and multimodal tasks
Mistral Medium 3
Kimi K3 is comparatively weak here — coding scores use Moonshot FrontierSWE, not standard SWE-Bench Verified
Efficient mid-tier deployment for production workloads
Mistral Medium 3
Kimi K3 is comparatively weak here — no independent benchmark reproduction yet at release
Lowest cost at scale
Mistral Medium 3
At $0.4/$2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Kimi K3
Its 1M window is about 8.2× larger than Mistral Medium 3's 128K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Mistral Medium 3
At $0.4/$2 per 1M tokens it undercuts Kimi K3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Kimi K3
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Kimi K3
Open weights let you run it on your own hardware; Mistral Medium 3 is API-only.
Anyone whose priority is largest open-weight model at release — 2.8t sparse moe, self-hostable
→ Kimi K3
It is specifically built for that.
Anyone whose priority is strong cost-to-capability at $0.40/$2.00
→ Mistral Medium 3
That is its strongest area.
An enterprise with regional data-residency rules
→ Mistral Medium 3 or Kimi K3
Origin (China vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Kimi K3: where it fits
Moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. Released July 27, 2026 by Moonshot AI, it is built for largest open-weight model at release — 2.8T sparse MoE, self-hostable, 1M-token context with native vision (text, image and video), vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness, and fresh-input pricing of $3/M (cached $0.30/M), flat across the full 1M context.
Its trade-offs are real: coding scores use Moonshot FrontierSWE, not standard SWE-Bench Verified, 2.8T params need serious hardware to self-host — weights are free, running is not, no independent benchmark reproduction yet at release, and image input but no audio or video. At $3 in / $15 out per million tokens, it sits in the mid price band.
Mistral Medium 3: where it fits
Mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. Released May 7, 2025 by Mistral AI, it is built for strong cost-to-capability at $0.40/$2.00, general reasoning, coding and multimodal tasks, efficient mid-tier deployment for production workloads, and text and image input.
Its trade-offs: a 128K context — smaller than the 1M-window flagships here, no published SWE-Bench Verified score, a mid-tier model, not a frontier reasoner, and proprietary, unlike Mistral's open-weight releases. At $0.4 in / $2 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. Kimi K3 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Mistral Medium 3 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 Kimi K3 and Mistral Medium 3 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, Kimi K3 leans toward largest open-weight model at release — 2.8t sparse moe, self-hostable while Mistral Medium 3 leans toward strong cost-to-capability at $0.40/$2.00, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Kimi K3 or Mistral Medium 3?
Kimi K3 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Mistral Medium 3 is API-metered at $0.4/$2 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?
Kimi K3 — 1M vs 128K, about 8.2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Kimi K3 and Mistral Medium 3 together?
Yes — a multi-model platform like LumiChats gives you Kimi K3, Mistral Medium 3 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, Kimi K3 or Mistral Medium 3?
Kimi K3 — released July 27, 2026, about 15 months after Mistral Medium 3.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.