Pick Claude Haiku 4.5 for fastest claude model or low-latency, high-volume api calls. Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. Choose Gemma 4 if you need self-hosting or data privacy; Claude Haiku 4.5 if you want a managed API.
Claude Haiku 4.5 (Anthropic) and Gemma 4 (Google) 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. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Gemma 4 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: Gemma 4 holds 1.3× more — 256K (~384 pages) vs 200K (~300 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Gemma 4 is the newer model by about 6 months (released April 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Claude Haiku 4.5
Gemma 4
Provider
Anthropic (US)
Google (US)
Released
October 15, 2025
April 2, 2026
Context window
200K (~300 pages)
256K (~384 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, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fastest Claude model: Claude Haiku 4.5 — A core design strength of Claude Haiku 4.5.
Low-latency, high-volume API calls: Claude Haiku 4.5 — A core design strength of Claude Haiku 4.5.
Real-time interactions: Claude Haiku 4.5 — A core design strength of Claude Haiku 4.5.
Self-hosted, data-private deployment: Gemma 4 — A core design strength of Gemma 4.
Running locally or on edge devices: Gemma 4 — A core design strength of Gemma 4.
Fine-tuning on your own data: Gemma 4 — A core design strength of Gemma 4.
Lowest cost at scale: Gemma 4 — 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: Gemma 4 — Its 256K window is about 1.3× larger, fitting roughly 384 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Gemma 4 — 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: Gemma 4 — Larger 256K window fits more in one prompt.
A team with data-privacy or self-hosting needs: Gemma 4 — 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-hosted, data-private deployment: Gemma 4 — 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, low-latency, high-volume API calls, real-time interactions, and cheapest Claude tier.
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.
Gemma 4: where it fits
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Released April 2, 2026 by Google, it is built for self-hosted, data-private deployment, running locally or on edge devices, fine-tuning on your own data, and multimodal tasks over a 256K context.
Its trade-offs: trails frontier closed models on the hardest tasks, and needs your own hardware to run. 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. Gemma 4 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 Gemma 4 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, Claude Haiku 4.5 leans toward fastest claude model while Gemma 4 leans toward self-hosted, data-private deployment, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Haiku 4.5 or Gemma 4?
Gemma 4 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?
Gemma 4 — 256K vs 200K, about 1.3× 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 Gemma 4 together?
Yes — a multi-model platform like LumiChats gives you Claude Haiku 4.5, Gemma 4 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 Gemma 4?
Gemma 4 — released April 2, 2026, about 6 months after Claude Haiku 4.5.
Claude Haiku 4.5 vs Gemma 4
Anthropic · US | Google · US · Updated June 2026
Quick verdict
Pick Claude Haiku 4.5 for fastest claude model or low-latency, high-volume api calls. Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. Choose Gemma 4 if you need self-hosting or data privacy; Claude Haiku 4.5 if you want a managed API.
Claude Haiku 4.5 (Anthropic) and Gemma 4 (Google) 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. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. 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: Gemma 4 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: Gemma 4 holds 1.3× more — 256K (~384 pages) vs 200K (~300 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Gemma 4 is the newer model by about 6 months (released April 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Claude Haiku 4.5
Gemma 4
Provider
Anthropic (US)
Google (US)
Released
October 15, 2025
April 2, 2026
Context window
200K (~300 pages)
256K (~384 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, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fastest Claude model
Claude Haiku 4.5
A core design strength of Claude Haiku 4.5.
Low-latency, high-volume API calls
Claude Haiku 4.5
A core design strength of Claude Haiku 4.5.
Real-time interactions
Claude Haiku 4.5
A core design strength of Claude Haiku 4.5.
Self-hosted, data-private deployment
Gemma 4
A core design strength of Gemma 4.
Running locally or on edge devices
Gemma 4
A core design strength of Gemma 4.
Fine-tuning on your own data
Gemma 4
A core design strength of Gemma 4.
Lowest cost at scale
Gemma 4
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
Gemma 4
Its 256K window is about 1.3× larger, fitting roughly 384 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemma 4
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
→ Gemma 4
Larger 256K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Gemma 4
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-hosted, data-private deployment
→ Gemma 4
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, low-latency, high-volume API calls, real-time interactions, and cheapest Claude tier.
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.
Gemma 4: where it fits
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Released April 2, 2026 by Google, it is built for self-hosted, data-private deployment, running locally or on edge devices, fine-tuning on your own data, and multimodal tasks over a 256K context.
Its trade-offs: trails frontier closed models on the hardest tasks, and needs your own hardware to run. 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. Gemma 4 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 Gemma 4 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.
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, Claude Haiku 4.5 leans toward fastest claude model while Gemma 4 leans toward self-hosted, data-private deployment, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Haiku 4.5 or Gemma 4?
Gemma 4 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?
Gemma 4 — 256K vs 200K, about 1.3× 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 Gemma 4 together?
Yes — a multi-model platform like LumiChats gives you Claude Haiku 4.5, Gemma 4 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 Gemma 4?
Gemma 4 — released April 2, 2026, about 6 months after Claude Haiku 4.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.