Pick DeepSeek R1 for open-weight reasoning model or transparent chain-of-thought. Pick Mistral Medium 3 for strong cost-to-capability at $0.40/$2.00 or general reasoning, coding and multimodal tasks. Choose DeepSeek R1 if you need self-hosting or data privacy; Mistral Medium 3 if you want a managed API.
DeepSeek R1 (DeepSeek, 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. DeepSeek R1 is the open-weight reasoning model that reset price expectations in early 2025. 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 and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: Mistral Medium 3 is about 1.4× cheaper on input ($0.4/$2 per 1M tokens vs $0.55/$2.19 per 1M tokens) — modest, but it adds up at steady volume.
Context window: both advertise 128K (~192 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
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 China-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
DeepSeek R1
Mistral Medium 3
Provider
DeepSeek (China)
Mistral AI (France)
Released
January 2025
May 7, 2025
Context window
128K (~192 pages)
128K (~192 pages)
Price (in/out)
$0.55/$2.19 per 1M tokens
$0.4/$2 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Open-weight reasoning model: DeepSeek R1 — Open weights make this possible at all — Mistral Medium 3 is API-only, so it cannot leave the vendor's servers.
Transparent chain-of-thought: DeepSeek R1 — The open-weight reasoning model that reset price expectations in early 2025 — and its weights are open while Mistral Medium 3 is API-only.
Low cost: DeepSeek R1 — DeepSeek R1 lists low cost among its strengths; Mistral Medium 3 does not.
Strong cost-to-capability at $0.40/$2.00: Mistral Medium 3 — At $0.4/$2 per 1M tokens it undercuts DeepSeek R1 ($0.55/$2.19 per 1M tokens), and that gap compounds at volume.
General reasoning, coding and multimodal tasks: 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 runs cheaper at $0.4/$2 per 1M tokens.
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.
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.
Which should you pick?
A cost-sensitive startup shipping high volume: Mistral Medium 3 — At $0.4/$2 per 1M tokens it undercuts DeepSeek R1, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs: DeepSeek R1 — Open weights let you run it on your own hardware; Mistral Medium 3 is API-only.
Anyone whose priority is open-weight reasoning model: DeepSeek R1 — 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 DeepSeek R1 — Origin (China vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
DeepSeek R1: where it fits
The open-weight reasoning model that reset price expectations in early 2025. Released January 2025 by DeepSeek, it is built for open-weight reasoning model, transparent chain-of-thought, low cost, and strong maths and code.
Its trade-offs are real: older than V4, smaller 128K context, and text/code focused. At $0.55 in / $2.19 out per million tokens, it sits in the budget 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. DeepSeek R1 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 DeepSeek R1 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, DeepSeek R1 leans toward open-weight reasoning model 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, DeepSeek R1 or Mistral Medium 3?
DeepSeek R1 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?
Both advertise 128K (~192 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both DeepSeek R1 and Mistral Medium 3 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek R1, 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, DeepSeek R1 or Mistral Medium 3?
Mistral Medium 3 — released May 7, 2025, about 4 months after DeepSeek R1.
DeepSeek R1 vs Mistral Medium 3
DeepSeek · China | Mistral AI · France · Updated June 2026
Quick verdict
Pick DeepSeek R1 for open-weight reasoning model or transparent chain-of-thought. Pick Mistral Medium 3 for strong cost-to-capability at $0.40/$2.00 or general reasoning, coding and multimodal tasks. Choose DeepSeek R1 if you need self-hosting or data privacy; Mistral Medium 3 if you want a managed API.
DeepSeek R1 (DeepSeek, 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. DeepSeek R1 is the open-weight reasoning model that reset price expectations in early 2025. 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 and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Mistral Medium 3 is about 1.4× cheaper on input ($0.4/$2 per 1M tokens vs $0.55/$2.19 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: both advertise 128K (~192 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸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 China-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
DeepSeek R1
Mistral Medium 3
Provider
DeepSeek (China)
Mistral AI (France)
Released
January 2025
May 7, 2025
Context window
128K (~192 pages)
128K (~192 pages)
Price (in/out)
$0.55/$2.19 per 1M tokens
$0.4/$2 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Open-weight reasoning model
DeepSeek R1
Open weights make this possible at all — Mistral Medium 3 is API-only, so it cannot leave the vendor's servers.
Transparent chain-of-thought
DeepSeek R1
The open-weight reasoning model that reset price expectations in early 2025 — and its weights are open while Mistral Medium 3 is API-only.
Low cost
DeepSeek R1
DeepSeek R1 lists low cost among its strengths; Mistral Medium 3 does not.
Strong cost-to-capability at $0.40/$2.00
Mistral Medium 3
At $0.4/$2 per 1M tokens it undercuts DeepSeek R1 ($0.55/$2.19 per 1M tokens), and that gap compounds at volume.
General reasoning, coding and multimodal tasks
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 runs cheaper at $0.4/$2 per 1M tokens.
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.
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.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Mistral Medium 3
At $0.4/$2 per 1M tokens it undercuts DeepSeek R1, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ DeepSeek R1
Open weights let you run it on your own hardware; Mistral Medium 3 is API-only.
Anyone whose priority is open-weight reasoning model
→ DeepSeek R1
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 DeepSeek R1
Origin (China vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
DeepSeek R1: where it fits
The open-weight reasoning model that reset price expectations in early 2025. Released January 2025 by DeepSeek, it is built for open-weight reasoning model, transparent chain-of-thought, low cost, and strong maths and code.
Its trade-offs are real: older than V4, smaller 128K context, and text/code focused. At $0.55 in / $2.19 out per million tokens, it sits in the budget 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. DeepSeek R1 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 DeepSeek R1 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.
Is DeepSeek R1 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, DeepSeek R1 leans toward open-weight reasoning model 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, DeepSeek R1 or Mistral Medium 3?
DeepSeek R1 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?
Both advertise 128K (~192 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both DeepSeek R1 and Mistral Medium 3 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek R1, 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, DeepSeek R1 or Mistral Medium 3?
Mistral Medium 3 — released May 7, 2025, about 4 months after DeepSeek R1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.