Pick Claude Haiku 4.5 for fastest claude model or near-frontier coding for its tier — 73.3% on swe-bench verified. Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high). Choose gpt-oss-120b if you need self-hosting or data privacy; Claude Haiku 4.5 if you want a managed API.
Claude Haiku 4.5 (Anthropic) and gpt-oss-120b (OpenAI) are two of the models people most often weigh against each other in 2026. Claude Haiku 4.5 is anthropic's fastest, most compact model — built for speed and volume. 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. They diverge most on price, context window, open vs. closed weights and coding benchmarks — 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 Claude Haiku 4.5 is API-metered at $1/$5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: Claude Haiku 4.5 holds 1.5× more — 200K (~300 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.
Coding: Claude Haiku 4.5 leads SWE-Bench Verified by 10.9 points (73.3% vs 62.4%) — a real edge on hard, real-world software tasks.
Recency: Claude Haiku 4.5 is the newer model by about 2 months (released October 15, 2025), usually meaning fresher training data and capabilities.
Specifications
Spec
Claude Haiku 4.5
gpt-oss-120b
Provider
Anthropic (US)
OpenAI (US)
Released
October 15, 2025
August 5, 2025
Context window
200K (~300 pages)
131K (~197 pages)
Price (in/out)
$1/$5 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
73.3%
62.4%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fastest Claude model: Claude Haiku 4.5 — gpt-oss-120b is comparatively weak here — 131K context and 5.1B active params trail the largest frontier closed models
Near-frontier coding for its tier — 73.3% on SWE-Bench Verified: Claude Haiku 4.5 — It scores 73.3% on SWE-Bench Verified against gpt-oss-120b's 62.4% — a 10.9-point edge on real repository work.
Low-latency, high-volume API calls: Claude Haiku 4.5 — Anthropic's fastest, most compact model — built for speed and volume — and it leads SWE-Bench Verified 73.3% to 62.4%.
Self-hostable on a single 80GB H100 GPU via MXFP4: gpt-oss-120b — Open weights make this possible at all — Claude Haiku 4.5 is API-only, so it cannot leave the vendor's servers.
Configurable reasoning depth (low/medium/high): gpt-oss-120b — Claude Haiku 4.5 is comparatively weak here — not for deep reasoning
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 its weights are open while Claude Haiku 4.5 is API-only.
Lowest cost at scale: gpt-oss-120b — Its weights are open, so at volume you pay for your own hardware instead of Claude Haiku 4.5's $1/$5 per 1M tokens.
Largest single-prompt input: Claude Haiku 4.5 — Its 200K window is about 1.5× larger than gpt-oss-120b's 131K, fitting roughly 300 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 Claude Haiku 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Claude Haiku 4.5 — Larger 200K 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; Claude Haiku 4.5 is API-only.
Anyone whose priority is fastest claude model: Claude Haiku 4.5 — It is specifically built for that.
Anyone whose priority is self-hostable on a single 80gb h100 gpu via mxfp4: gpt-oss-120b — That is its strongest area.
Claude Haiku 4.5: where it fits
Anthropic's fastest, most compact model — built for speed and volume. Released October 15, 2025 by Anthropic, it is built for fastest Claude model, near-frontier coding for its tier — 73.3% on SWE-Bench Verified, low-latency, high-volume API calls, and cheapest Claude tier at $1/$5.
Its trade-offs are real: smallest context in the family (200K), and not for deep reasoning. At $1 in / $5 out per million tokens, it sits in the budget price band.
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: 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.
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. Claude Haiku 4.5 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 Claude Haiku 4.5 or gpt-oss-120b better for coding?
On SWE-Bench Verified, Claude Haiku 4.5 scores 73.3% and gpt-oss-120b scores 62.4% — Claude Haiku 4.5 has the measurable edge.
Which is cheaper, Claude Haiku 4.5 or gpt-oss-120b?
gpt-oss-120b is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Haiku 4.5 is API-metered at $1/$5 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?
Claude Haiku 4.5 — 200K vs 131K, about 1.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Haiku 4.5 and gpt-oss-120b together?
Yes — a multi-model platform like LumiChats gives you Claude Haiku 4.5, gpt-oss-120b 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, Claude Haiku 4.5 or gpt-oss-120b?
Claude Haiku 4.5 — released October 15, 2025, about 2 months after gpt-oss-120b.
Claude Haiku 4.5 vs gpt-oss-120b
Anthropic · US | OpenAI · US · Updated June 2026
Quick verdict
Pick Claude Haiku 4.5 for fastest claude model or near-frontier coding for its tier — 73.3% on swe-bench verified. Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high). Choose gpt-oss-120b if you need self-hosting or data privacy; Claude Haiku 4.5 if you want a managed API.
Claude Haiku 4.5 (Anthropic) and gpt-oss-120b (OpenAI) are two of the models people most often weigh against each other in 2026. Claude Haiku 4.5 is anthropic's fastest, most compact model — built for speed and volume. 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. They diverge most on price, context window, open vs. closed weights and coding benchmarks — 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 Claude Haiku 4.5 is API-metered at $1/$5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: Claude Haiku 4.5 holds 1.5× more — 200K (~300 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.
▸Coding: Claude Haiku 4.5 leads SWE-Bench Verified by 10.9 points (73.3% vs 62.4%) — a real edge on hard, real-world software tasks.
▸Recency: Claude Haiku 4.5 is the newer model by about 2 months (released October 15, 2025), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Claude Haiku 4.5
gpt-oss-120b
Provider
Anthropic (US)
OpenAI (US)
Released
October 15, 2025
August 5, 2025
Context window
200K (~300 pages)
131K (~197 pages)
Price (in/out)
$1/$5 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
73.3%
62.4%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fastest Claude model
Claude Haiku 4.5
gpt-oss-120b is comparatively weak here — 131K context and 5.1B active params trail the largest frontier closed models
Near-frontier coding for its tier — 73.3% on SWE-Bench Verified
Claude Haiku 4.5
It scores 73.3% on SWE-Bench Verified against gpt-oss-120b's 62.4% — a 10.9-point edge on real repository work.
Low-latency, high-volume API calls
Claude Haiku 4.5
Anthropic's fastest, most compact model — built for speed and volume — and it leads SWE-Bench Verified 73.3% to 62.4%.
Self-hostable on a single 80GB H100 GPU via MXFP4
gpt-oss-120b
Open weights make this possible at all — Claude Haiku 4.5 is API-only, so it cannot leave the vendor's servers.
Configurable reasoning depth (low/medium/high)
gpt-oss-120b
Claude Haiku 4.5 is comparatively weak here — not for deep reasoning
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 its weights are open while Claude Haiku 4.5 is API-only.
Lowest cost at scale
gpt-oss-120b
Its weights are open, so at volume you pay for your own hardware instead of Claude Haiku 4.5's $1/$5 per 1M tokens.
Largest single-prompt input
Claude Haiku 4.5
Its 200K window is about 1.5× larger than gpt-oss-120b's 131K, fitting roughly 300 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 Claude Haiku 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Claude Haiku 4.5
Larger 200K 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; Claude Haiku 4.5 is API-only.
Anyone whose priority is fastest claude model
→ Claude Haiku 4.5
It is specifically built for that.
Anyone whose priority is self-hostable on a single 80gb h100 gpu via mxfp4
→ gpt-oss-120b
That is its strongest area.
Claude Haiku 4.5: where it fits
Anthropic's fastest, most compact model — built for speed and volume. Released October 15, 2025 by Anthropic, it is built for fastest Claude model, near-frontier coding for its tier — 73.3% on SWE-Bench Verified, low-latency, high-volume API calls, and cheapest Claude tier at $1/$5.
Its trade-offs are real: smallest context in the family (200K), and not for deep reasoning. At $1 in / $5 out per million tokens, it sits in the budget price band.
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: 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.
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. Claude Haiku 4.5 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 Claude Haiku 4.5 and gpt-oss-120b 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 Claude Haiku 4.5 or gpt-oss-120b better for coding?
On SWE-Bench Verified, Claude Haiku 4.5 scores 73.3% and gpt-oss-120b scores 62.4% — Claude Haiku 4.5 has the measurable edge.
Which is cheaper, Claude Haiku 4.5 or gpt-oss-120b?
gpt-oss-120b is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Haiku 4.5 is API-metered at $1/$5 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?
Claude Haiku 4.5 — 200K vs 131K, about 1.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Haiku 4.5 and gpt-oss-120b together?
Yes — a multi-model platform like LumiChats gives you Claude Haiku 4.5, gpt-oss-120b 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, Claude Haiku 4.5 or gpt-oss-120b?
Claude Haiku 4.5 — released October 15, 2025, about 2 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.