Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high). Pick Mistral Medium 3 for strong cost-to-capability at $0.40/$2.00 or general reasoning, coding and multimodal tasks. Choose gpt-oss-120b if you need self-hosting or data privacy; Mistral Medium 3 if you want a managed API.
gpt-oss-120b (OpenAI, US) 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. gpt-oss-120b is openAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. 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
Cost model: gpt-oss-120b ships open weights you can self-host (hardware cost only, no per-token fee), while Mistral Medium 3 is API-metered at $0.4/$2 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: 131K vs 128K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: gpt-oss-120b is the newer model by about 3 months (released August 5, 2025), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
gpt-oss-120b
Mistral Medium 3
Provider
OpenAI (US)
Mistral AI (France)
Released
August 5, 2025
May 7, 2025
Context window
131K (~197 pages)
128K (~192 pages)
Price (in/out)
Open weight (self-host / free)
$0.4/$2 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, code
SWE-Bench Verified
62.4%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Self-hostable on a single 80GB H100 GPU via MXFP4: gpt-oss-120b — Open weights make this possible at all — Mistral Medium 3 is API-only, so it cannot leave the vendor's servers.
Configurable reasoning depth (low/medium/high): gpt-oss-120b — OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use — and its weights are open while Mistral Medium 3 is API-only.
Agentic tool use, function calling, and code execution: gpt-oss-120b — OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use — and it is the newer of the two.
Strong cost-to-capability at $0.40/$2.00: Mistral Medium 3 — Mistral Medium 3 lists strong cost-to-capability at $0.40/$2.00 among its strengths; gpt-oss-120b does not.
General reasoning, coding and multimodal tasks: Mistral Medium 3 — Mistral Medium 3 lists general reasoning, coding and multimodal tasks among its strengths; gpt-oss-120b does not.
Efficient mid-tier deployment for production workloads: Mistral Medium 3 — Mistral Medium 3 lists efficient mid-tier deployment for production workloads among its strengths; gpt-oss-120b does not.
Lowest cost at scale: gpt-oss-120b — Its weights are open, so at volume you pay for your own hardware instead of Mistral Medium 3's $0.4/$2 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: gpt-oss-120b — At Open weight (self-host / free) it undercuts Mistral Medium 3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: gpt-oss-120b — Larger 131K window fits more in one prompt.
A team with data-privacy or self-hosting needs: gpt-oss-120b — Open weights let you run it on your own hardware; Mistral Medium 3 is API-only.
Anyone whose priority is self-hostable on a single 80gb h100 gpu via mxfp4: gpt-oss-120b — 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: gpt-oss-120b or Mistral Medium 3 — Origin (US vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
gpt-oss-120b: where it fits
OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. Released August 5, 2025 by OpenAI, it is built for self-hostable on a single 80GB H100 GPU via MXFP4, configurable reasoning depth (low/medium/high), agentic tool use, function calling, and code execution, and full chain-of-thought visibility for debugging.
Its trade-offs are real: text-only, no image, audio, or video input, and 131K context and 5.1B active params trail the largest frontier closed models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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. gpt-oss-120b 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 gpt-oss-120b or Mistral Medium 3 better for coding?
Public SWE-Bench figures are not available for Mistral Medium 3, so the honest test is your own repository — run an identical real bug through both. By design, gpt-oss-120b leans toward self-hostable on a single 80gb h100 gpu via mxfp4 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, gpt-oss-120b or Mistral Medium 3?
gpt-oss-120b 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?
Effectively neither — 131K vs 128K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both gpt-oss-120b and Mistral Medium 3 together?
Yes — a multi-model platform like LumiChats gives you gpt-oss-120b, 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, gpt-oss-120b or Mistral Medium 3?
gpt-oss-120b — released August 5, 2025, about 3 months after Mistral Medium 3.
gpt-oss-120b vs Mistral Medium 3
OpenAI · US | Mistral AI · France · Updated June 2026
Quick verdict
Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high). Pick Mistral Medium 3 for strong cost-to-capability at $0.40/$2.00 or general reasoning, coding and multimodal tasks. Choose gpt-oss-120b if you need self-hosting or data privacy; Mistral Medium 3 if you want a managed API.
gpt-oss-120b (OpenAI, US) 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. gpt-oss-120b is openAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. 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
▸Cost model: gpt-oss-120b ships open weights you can self-host (hardware cost only, no per-token fee), while Mistral Medium 3 is API-metered at $0.4/$2 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: 131K vs 128K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: gpt-oss-120b is the newer model by about 3 months (released August 5, 2025), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
gpt-oss-120b
Mistral Medium 3
Provider
OpenAI (US)
Mistral AI (France)
Released
August 5, 2025
May 7, 2025
Context window
131K (~197 pages)
128K (~192 pages)
Price (in/out)
Open weight (self-host / free)
$0.4/$2 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, code
SWE-Bench Verified
62.4%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Self-hostable on a single 80GB H100 GPU via MXFP4
gpt-oss-120b
Open weights make this possible at all — Mistral Medium 3 is API-only, so it cannot leave the vendor's servers.
Configurable reasoning depth (low/medium/high)
gpt-oss-120b
OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use — and its weights are open while Mistral Medium 3 is API-only.
Agentic tool use, function calling, and code execution
gpt-oss-120b
OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use — and it is the newer of the two.
Strong cost-to-capability at $0.40/$2.00
Mistral Medium 3
Mistral Medium 3 lists strong cost-to-capability at $0.40/$2.00 among its strengths; gpt-oss-120b does not.
General reasoning, coding and multimodal tasks
Mistral Medium 3
Mistral Medium 3 lists general reasoning, coding and multimodal tasks among its strengths; gpt-oss-120b does not.
Efficient mid-tier deployment for production workloads
Mistral Medium 3
Mistral Medium 3 lists efficient mid-tier deployment for production workloads among its strengths; gpt-oss-120b does not.
Lowest cost at scale
gpt-oss-120b
Its weights are open, so at volume you pay for your own hardware instead of Mistral Medium 3's $0.4/$2 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ gpt-oss-120b
At Open weight (self-host / free) it undercuts Mistral Medium 3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ gpt-oss-120b
Larger 131K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ gpt-oss-120b
Open weights let you run it on your own hardware; Mistral Medium 3 is API-only.
Anyone whose priority is self-hostable on a single 80gb h100 gpu via mxfp4
→ gpt-oss-120b
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
→ gpt-oss-120b or Mistral Medium 3
Origin (US vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
gpt-oss-120b: where it fits
OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. Released August 5, 2025 by OpenAI, it is built for self-hostable on a single 80GB H100 GPU via MXFP4, configurable reasoning depth (low/medium/high), agentic tool use, function calling, and code execution, and full chain-of-thought visibility for debugging.
Its trade-offs are real: text-only, no image, audio, or video input, and 131K context and 5.1B active params trail the largest frontier closed models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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. gpt-oss-120b 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 gpt-oss-120b 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 gpt-oss-120b or Mistral Medium 3 better for coding?
Public SWE-Bench figures are not available for Mistral Medium 3, so the honest test is your own repository — run an identical real bug through both. By design, gpt-oss-120b leans toward self-hostable on a single 80gb h100 gpu via mxfp4 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, gpt-oss-120b or Mistral Medium 3?
gpt-oss-120b 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?
Effectively neither — 131K vs 128K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both gpt-oss-120b and Mistral Medium 3 together?
Yes — a multi-model platform like LumiChats gives you gpt-oss-120b, 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, gpt-oss-120b or Mistral Medium 3?
gpt-oss-120b — released August 5, 2025, about 3 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.