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 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier or 128b dense open-weight model — self-hostable. On a tight budget at scale, gpt-oss-120b is the value pick.
gpt-oss-120b (OpenAI, US) and Mistral Medium 3.5 (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 3.5 is mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: Mistral Medium 3.5 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 Medium 3.5 is the newer model by about 9 months (released April 29, 2026), 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 3.5
Provider
OpenAI (US)
Mistral AI (France)
Released
August 5, 2025
April 29, 2026
Context window
131K (~197 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
$1.5/$7.5 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 — gpt-oss-120b lists self-hostable on a single 80GB H100 GPU via MXFP4 among its strengths; Mistral Medium 3.5 does not.
Configurable reasoning depth (low/medium/high): gpt-oss-120b — gpt-oss-120b lists configurable reasoning depth (low/medium/high) among its strengths; Mistral Medium 3.5 does not.
Agentic tool use, function calling, and code execution: gpt-oss-120b — gpt-oss-120b lists agentic tool use, function calling, and code execution among its strengths; Mistral Medium 3.5 does not.
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier: Mistral Medium 3.5 — Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30) — and it carries the larger 256K context.
128B dense open-weight model — self-hostable: Mistral Medium 3.5 — gpt-oss-120b is comparatively weak here — 131K context and 5.1B active params trail the largest frontier closed models
Unifies reasoning and coding into one model with an adjustable reasoning effort: Mistral Medium 3.5 — Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30) — and it is the newer of the two.
Lowest cost at scale: gpt-oss-120b — Its weights are open, so at volume you pay for your own hardware instead of Mistral Medium 3.5's $1.5/$7.5 per 1M tokens.
Largest single-prompt input: Mistral Medium 3.5 — Its 256K window is about 2× larger than gpt-oss-120b's 131K, 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 Medium 3.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Mistral Medium 3.5 — 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 strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier: Mistral Medium 3.5 — That is its strongest area.
An enterprise with regional data-residency rules: gpt-oss-120b or Mistral Medium 3.5 — 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 3.5: where it fits
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). Released April 29, 2026 by Mistral AI, it is built for strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier, 128B dense open-weight model — self-hostable, unifies reasoning and coding into one model with an adjustable reasoning effort, and 256K context with text and image input.
Its trade-offs: below the absolute frontier — a value/efficiency pick, not a flagship-beater, output pricing ($7.50/M) is higher than the cheapest Chinese rivals, license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use, and no native video or audio. At $1.5 in / $7.5 out per million tokens, it sits in the mid 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 Medium 3.5 (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 Medium 3.5 better for coding?
Public SWE-Bench figures are not available for Mistral Medium 3.5, 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 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, gpt-oss-120b or Mistral Medium 3.5?
gpt-oss-120b is cheaper — Open weight (self-host / free) vs $1.5/$7.5 per 1M tokens.
Which has the bigger context window?
Mistral Medium 3.5 — 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 Medium 3.5 together?
Yes — a multi-model platform like LumiChats gives you gpt-oss-120b, Mistral Medium 3.5 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 3.5?
Mistral Medium 3.5 — released April 29, 2026, about 9 months after gpt-oss-120b.
gpt-oss-120b vs Mistral Medium 3.5
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 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier or 128b dense open-weight model — self-hostable. On a tight budget at scale, gpt-oss-120b is the value pick.
gpt-oss-120b (OpenAI, US) and Mistral Medium 3.5 (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 3.5 is mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: Mistral Medium 3.5 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 Medium 3.5 is the newer model by about 9 months (released April 29, 2026), 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 3.5
Provider
OpenAI (US)
Mistral AI (France)
Released
August 5, 2025
April 29, 2026
Context window
131K (~197 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
$1.5/$7.5 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
gpt-oss-120b lists self-hostable on a single 80GB H100 GPU via MXFP4 among its strengths; Mistral Medium 3.5 does not.
Configurable reasoning depth (low/medium/high)
gpt-oss-120b
gpt-oss-120b lists configurable reasoning depth (low/medium/high) among its strengths; Mistral Medium 3.5 does not.
Agentic tool use, function calling, and code execution
gpt-oss-120b
gpt-oss-120b lists agentic tool use, function calling, and code execution among its strengths; Mistral Medium 3.5 does not.
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier
Mistral Medium 3.5
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30) — and it carries the larger 256K context.
128B dense open-weight model — self-hostable
Mistral Medium 3.5
gpt-oss-120b is comparatively weak here — 131K context and 5.1B active params trail the largest frontier closed models
Unifies reasoning and coding into one model with an adjustable reasoning effort
Mistral Medium 3.5
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30) — and it is the newer of the two.
Lowest cost at scale
gpt-oss-120b
Its weights are open, so at volume you pay for your own hardware instead of Mistral Medium 3.5's $1.5/$7.5 per 1M tokens.
Largest single-prompt input
Mistral Medium 3.5
Its 256K window is about 2× larger than gpt-oss-120b's 131K, 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 Medium 3.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Mistral Medium 3.5
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 strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier
→ Mistral Medium 3.5
That is its strongest area.
An enterprise with regional data-residency rules
→ gpt-oss-120b or Mistral Medium 3.5
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 3.5: where it fits
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). Released April 29, 2026 by Mistral AI, it is built for strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier, 128B dense open-weight model — self-hostable, unifies reasoning and coding into one model with an adjustable reasoning effort, and 256K context with text and image input.
Its trade-offs: below the absolute frontier — a value/efficiency pick, not a flagship-beater, output pricing ($7.50/M) is higher than the cheapest Chinese rivals, license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use, and no native video or audio. At $1.5 in / $7.5 out per million tokens, it sits in the mid 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 Medium 3.5 (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 Medium 3.5 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 3.5 better for coding?
Public SWE-Bench figures are not available for Mistral Medium 3.5, 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 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, gpt-oss-120b or Mistral Medium 3.5?
gpt-oss-120b is cheaper — Open weight (self-host / free) vs $1.5/$7.5 per 1M tokens.
Which has the bigger context window?
Mistral Medium 3.5 — 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 Medium 3.5 together?
Yes — a multi-model platform like LumiChats gives you gpt-oss-120b, Mistral Medium 3.5 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 3.5?
Mistral Medium 3.5 — released April 29, 2026, about 9 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.