Pick Mistral Medium 3 for strong cost-to-capability at $0.40/$2.00 or general reasoning, coding and multimodal tasks. Pick Microsoft Phi-4 for strong reasoning for a small 14b open-weight model or mit-licensed — fully self-hostable at no per-token cost. Choose Microsoft Phi-4 if you need self-hosting or data privacy; Mistral Medium 3 if you want a managed API.
Mistral Medium 3 (Mistral AI, France) and Microsoft Phi-4 (Microsoft, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. Microsoft Phi-4 is microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: Microsoft Phi-4 is about 5.7× cheaper on input ($0.07/$0.14 per 1M tokens vs $0.4/$2 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Mistral Medium 3 holds 7.8× more — 128K (~192 pages) vs 16K (~25 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Mistral Medium 3 is the newer model by about 4 months (released May 7, 2025), usually meaning fresher training data and capabilities.
Ecosystem: this is a France-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Mistral Medium 3
Microsoft Phi-4
Provider
Mistral AI (France)
Microsoft (US)
Released
May 7, 2025
January 10, 2025
Context window
128K (~192 pages)
16K (~25 pages)
Price (in/out)
$0.4/$2 per 1M tokens
$0.07/$0.14 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong cost-to-capability at $0.40/$2.00: Mistral Medium 3 — Mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier — and it carries the larger 128K context.
General reasoning, coding and multimodal tasks: Mistral Medium 3 — Microsoft Phi-4 is comparatively weak here — an early-2025 small model, outclassed on hard tasks by 2026 flagships
Efficient mid-tier deployment for production workloads: Mistral Medium 3 — Mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier — and it is the newer of the two.
Strong reasoning for a small 14B open-weight model: Microsoft Phi-4 — Open weights make this possible at all — Mistral Medium 3 is API-only, so it cannot leave the vendor's servers.
MIT-licensed — fully self-hostable at no per-token cost: Microsoft Phi-4 — At $0.07/$0.14 per 1M tokens it undercuts Mistral Medium 3 ($0.4/$2 per 1M tokens), and that gap compounds at volume.
Runs on modest or local hardware: Microsoft Phi-4 — Microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only — and it runs cheaper at $0.07/$0.14 per 1M tokens.
Lowest cost at scale: Microsoft Phi-4 — At $0.07/$0.14 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Mistral Medium 3 — Its 128K window is about 7.8× larger than Microsoft Phi-4's 16K, fitting roughly 192 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Microsoft Phi-4 — At $0.07/$0.14 per 1M tokens it undercuts Mistral Medium 3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Mistral Medium 3 — Larger 128K window fits more in one prompt.
A team with data-privacy or self-hosting needs: Microsoft Phi-4 — Open weights let you run it on your own hardware; Mistral Medium 3 is API-only.
Anyone whose priority is strong cost-to-capability at $0.40/$2.00: Mistral Medium 3 — It is specifically built for that.
Anyone whose priority is strong reasoning for a small 14b open-weight model: Microsoft Phi-4 — That is its strongest area.
An enterprise with regional data-residency rules: Microsoft Phi-4 or Mistral Medium 3 — Origin (France vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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 are real: 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.
Microsoft Phi-4: where it fits
Microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only. Released January 10, 2025 by Microsoft, it is built for strong reasoning for a small 14B open-weight model, mIT-licensed — fully self-hostable at no per-token cost, runs on modest or local hardware, and very cheap hosted inference at about $0.07/$0.14.
Its trade-offs: a tiny 16K context — by far the smallest window in this comparison, text only — no image, audio or video input, an early-2025 small model, outclassed on hard tasks by 2026 flagships, and no first-party per-token API; hosted prices are third-party. At $0.07 in / $0.14 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. Microsoft Phi-4 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 Mistral Medium 3 or Microsoft Phi-4 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, Mistral Medium 3 leans toward strong cost-to-capability at $0.40/$2.00 while Microsoft Phi-4 leans toward strong reasoning for a small 14b open-weight model, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Mistral Medium 3 or Microsoft Phi-4?
Microsoft Phi-4 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?
Mistral Medium 3 — 128K vs 16K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Mistral Medium 3 and Microsoft Phi-4 together?
Yes — a multi-model platform like LumiChats gives you Mistral Medium 3, Microsoft Phi-4 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, Mistral Medium 3 or Microsoft Phi-4?
Mistral Medium 3 — released May 7, 2025, about 4 months after Microsoft Phi-4.
Mistral Medium 3 vs Microsoft Phi-4
Mistral AI · France | Microsoft · US · Updated June 2026
Quick verdict
Pick Mistral Medium 3 for strong cost-to-capability at $0.40/$2.00 or general reasoning, coding and multimodal tasks. Pick Microsoft Phi-4 for strong reasoning for a small 14b open-weight model or mit-licensed — fully self-hostable at no per-token cost. Choose Microsoft Phi-4 if you need self-hosting or data privacy; Mistral Medium 3 if you want a managed API.
Mistral Medium 3 (Mistral AI, France) and Microsoft Phi-4 (Microsoft, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. Microsoft Phi-4 is microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only. 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: Microsoft Phi-4 is about 5.7× cheaper on input ($0.07/$0.14 per 1M tokens vs $0.4/$2 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Mistral Medium 3 holds 7.8× more — 128K (~192 pages) vs 16K (~25 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Mistral Medium 3 is the newer model by about 4 months (released May 7, 2025), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a France-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Mistral Medium 3
Microsoft Phi-4
Provider
Mistral AI (France)
Microsoft (US)
Released
May 7, 2025
January 10, 2025
Context window
128K (~192 pages)
16K (~25 pages)
Price (in/out)
$0.4/$2 per 1M tokens
$0.07/$0.14 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong cost-to-capability at $0.40/$2.00
Mistral Medium 3
Mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier — and it carries the larger 128K context.
General reasoning, coding and multimodal tasks
Mistral Medium 3
Microsoft Phi-4 is comparatively weak here — an early-2025 small model, outclassed on hard tasks by 2026 flagships
Efficient mid-tier deployment for production workloads
Mistral Medium 3
Mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier — and it is the newer of the two.
Strong reasoning for a small 14B open-weight model
Microsoft Phi-4
Open weights make this possible at all — Mistral Medium 3 is API-only, so it cannot leave the vendor's servers.
MIT-licensed — fully self-hostable at no per-token cost
Microsoft Phi-4
At $0.07/$0.14 per 1M tokens it undercuts Mistral Medium 3 ($0.4/$2 per 1M tokens), and that gap compounds at volume.
Runs on modest or local hardware
Microsoft Phi-4
Microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only — and it runs cheaper at $0.07/$0.14 per 1M tokens.
Lowest cost at scale
Microsoft Phi-4
At $0.07/$0.14 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Mistral Medium 3
Its 128K window is about 7.8× larger than Microsoft Phi-4's 16K, fitting roughly 192 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Microsoft Phi-4
At $0.07/$0.14 per 1M tokens it undercuts Mistral Medium 3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Mistral Medium 3
Larger 128K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Microsoft Phi-4
Open weights let you run it on your own hardware; Mistral Medium 3 is API-only.
Anyone whose priority is strong cost-to-capability at $0.40/$2.00
→ Mistral Medium 3
It is specifically built for that.
Anyone whose priority is strong reasoning for a small 14b open-weight model
→ Microsoft Phi-4
That is its strongest area.
An enterprise with regional data-residency rules
→ Microsoft Phi-4 or Mistral Medium 3
Origin (France vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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 are real: 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.
Microsoft Phi-4: where it fits
Microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only. Released January 10, 2025 by Microsoft, it is built for strong reasoning for a small 14B open-weight model, mIT-licensed — fully self-hostable at no per-token cost, runs on modest or local hardware, and very cheap hosted inference at about $0.07/$0.14.
Its trade-offs: a tiny 16K context — by far the smallest window in this comparison, text only — no image, audio or video input, an early-2025 small model, outclassed on hard tasks by 2026 flagships, and no first-party per-token API; hosted prices are third-party. At $0.07 in / $0.14 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. Microsoft Phi-4 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 Mistral Medium 3 and Microsoft Phi-4 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.
Is Mistral Medium 3 or Microsoft Phi-4 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, Mistral Medium 3 leans toward strong cost-to-capability at $0.40/$2.00 while Microsoft Phi-4 leans toward strong reasoning for a small 14b open-weight model, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Mistral Medium 3 or Microsoft Phi-4?
Microsoft Phi-4 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?
Mistral Medium 3 — 128K vs 16K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Mistral Medium 3 and Microsoft Phi-4 together?
Yes — a multi-model platform like LumiChats gives you Mistral Medium 3, Microsoft Phi-4 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, Mistral Medium 3 or Microsoft Phi-4?
Mistral Medium 3 — released May 7, 2025, about 4 months after Microsoft Phi-4.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.