Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high). Pick Mistral Large 3 for open-weight (apache 2.0), self-hostable or strong multilingual performance. On a tight budget at scale, gpt-oss-120b is the value pick.
gpt-oss-120b (OpenAI, US) and Mistral Large 3 (Mistral, 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 Large 3 is france's frontier contender — strong multilingual model with European data residency. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: Mistral Large 3 holds 2× more — 256K (~384 pages) vs 131K (~197 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 Large 3 is the newer model by about 4 months (released December 2, 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 Large 3
Provider
OpenAI (US)
Mistral (France)
Released
August 5, 2025
December 2, 2025
Context window
131K (~197 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
$0.5/$1.5 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
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 — A core design strength of gpt-oss-120b.
Configurable reasoning depth (low/medium/high): gpt-oss-120b — A core design strength of gpt-oss-120b.
Agentic tool use, function calling, and code execution: gpt-oss-120b — A core design strength of gpt-oss-120b.
Open-weight (Apache 2.0), self-hostable: Mistral Large 3 — A core design strength of Mistral Large 3.
Strong multilingual performance: Mistral Large 3 — A core design strength of Mistral Large 3.
Efficient inference: Mistral Large 3 — A core design strength of Mistral Large 3.
Lowest cost at scale: gpt-oss-120b — At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Mistral Large 3 — Its 256K window is about 2× larger, fitting roughly 384 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: gpt-oss-120b — At Open weight (self-host / free) it undercuts Mistral Large 3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Mistral Large 3 — Larger 256K window fits more in one prompt.
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 open-weight (apache 2.0), self-hostable: Mistral Large 3 — That is its strongest area.
An enterprise with regional data-residency rules: gpt-oss-120b or Mistral Large 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 Large 3: where it fits
France's frontier contender — strong multilingual model with European data residency. Released December 2, 2025 by Mistral, it is built for open-weight (Apache 2.0), self-hostable, strong multilingual performance, efficient inference, and function calling.
Its trade-offs: smaller context than US/China frontier, and less benchmark coverage. At $0.5 in / $1.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." gpt-oss-120b (US) and Mistral Large 3 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. gpt-oss-120b is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Frequently asked questions
Is gpt-oss-120b or Mistral Large 3 better for coding?
Public SWE-Bench figures are not available for Mistral Large 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 Large 3 leans toward open-weight (apache 2.0), self-hostable, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, gpt-oss-120b or Mistral Large 3?
gpt-oss-120b is cheaper — Open weight (self-host / free) vs $0.5/$1.5 per 1M tokens.
Which has the bigger context window?
Mistral Large 3 — 256K vs 131K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both gpt-oss-120b and Mistral Large 3 together?
Yes — a multi-model platform like LumiChats gives you gpt-oss-120b, Mistral Large 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 Large 3?
Mistral Large 3 — released December 2, 2025, about 4 months after gpt-oss-120b.
gpt-oss-120b vs Mistral Large 3
OpenAI · US | Mistral · 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 Large 3 for open-weight (apache 2.0), self-hostable or strong multilingual performance. On a tight budget at scale, gpt-oss-120b is the value pick.
gpt-oss-120b (OpenAI, US) and Mistral Large 3 (Mistral, 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 Large 3 is france's frontier contender — strong multilingual model with European data residency. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: Mistral Large 3 holds 2× more — 256K (~384 pages) vs 131K (~197 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 Large 3 is the newer model by about 4 months (released December 2, 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 Large 3
Provider
OpenAI (US)
Mistral (France)
Released
August 5, 2025
December 2, 2025
Context window
131K (~197 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
$0.5/$1.5 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
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
A core design strength of gpt-oss-120b.
Configurable reasoning depth (low/medium/high)
gpt-oss-120b
A core design strength of gpt-oss-120b.
Agentic tool use, function calling, and code execution
gpt-oss-120b
A core design strength of gpt-oss-120b.
Open-weight (Apache 2.0), self-hostable
Mistral Large 3
A core design strength of Mistral Large 3.
Strong multilingual performance
Mistral Large 3
A core design strength of Mistral Large 3.
Efficient inference
Mistral Large 3
A core design strength of Mistral Large 3.
Lowest cost at scale
gpt-oss-120b
At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Mistral Large 3
Its 256K window is about 2× larger, fitting roughly 384 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ gpt-oss-120b
At Open weight (self-host / free) it undercuts Mistral Large 3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Mistral Large 3
Larger 256K window fits more in one prompt.
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 open-weight (apache 2.0), self-hostable
→ Mistral Large 3
That is its strongest area.
An enterprise with regional data-residency rules
→ gpt-oss-120b or Mistral Large 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 Large 3: where it fits
France's frontier contender — strong multilingual model with European data residency. Released December 2, 2025 by Mistral, it is built for open-weight (Apache 2.0), self-hostable, strong multilingual performance, efficient inference, and function calling.
Its trade-offs: smaller context than US/China frontier, and less benchmark coverage. At $0.5 in / $1.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." gpt-oss-120b (US) and Mistral Large 3 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. gpt-oss-120b is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both gpt-oss-120b and Mistral Large 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 Large 3 better for coding?
Public SWE-Bench figures are not available for Mistral Large 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 Large 3 leans toward open-weight (apache 2.0), self-hostable, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, gpt-oss-120b or Mistral Large 3?
gpt-oss-120b is cheaper — Open weight (self-host / free) vs $0.5/$1.5 per 1M tokens.
Which has the bigger context window?
Mistral Large 3 — 256K vs 131K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both gpt-oss-120b and Mistral Large 3 together?
Yes — a multi-model platform like LumiChats gives you gpt-oss-120b, Mistral Large 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 Large 3?
Mistral Large 3 — released December 2, 2025, about 4 months after gpt-oss-120b.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.