Gemini 3.8 Flash vs Reflection Beam 1.0
Google DeepMind · US | Reflection AI · US · Updated June 2026
Quick verdict
Pick Gemini 3.8 Flash for long-horizon agentic coding (deepswe v1.1) or cost-efficient workhorse performance beating larger models at same price as 3.7 flash. Pick Reflection Beam 1.0 for 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0 or reflection claims 3-4x less inference compute than rival models (vendor claim). Choose Reflection Beam 1.0 if you need self-hosting or data privacy; Gemini 3.8 Flash if you want a managed API.
Gemini 3.8 Flash (Google DeepMind) and Reflection Beam 1.0 (Reflection AI) are two of the models people most often weigh against each other in 2026. Gemini 3.8 Flash is google's cost-efficient workhorse model released September 2, 2026, tuned for long-horizon coding and autonomous agents, launched alongside a restricted 'Cyber' variant for vulnerability research. Reflection Beam 1.0 is reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Cost model: Reflection Beam 1.0 ships open weights you can self-host (hardware cost only, no per-token fee), while Gemini 3.8 Flash is API-metered at $0.75/$3.75 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
- ▸Context window: both advertise 1M tokens (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: Reflection Beam 1.0 is the newer model by about 44 days (released October 16, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Gemini 3.8 Flash | Reflection Beam 1.0 |
|---|---|---|
| Provider | Google DeepMind (US) | Reflection AI (US) |
| Released | September 2, 2026 | October 16, 2026 |
| Context window | 1M tokens (~1,500 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | $0.75/$3.75 per 1M tokens | Open weight (self-host / free) |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, image, audio, video | text, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Long-horizon agentic coding (DeepSWE v1.1)
Gemini 3.8 Flash
Gemini 3.8 Flash lists long-horizon agentic coding (DeepSWE v1.1) among its strengths; Reflection Beam 1.0 does not.
Cost-efficient workhorse performance beating larger models at same price as 3.7 Flash
Gemini 3.8 Flash
Reflection Beam 1.0 is comparatively weak here — artificial Analysis Intelligence Index of 30, well below DeepSeek V4.1 Flash and GLM-5.3 (45)
Vals Finance Agent V2 benchmark (61.4%, ahead of Claude Opus 5's 58.6%); also leads a weak field on the Harvey legal benchmark (10.0%)
Gemini 3.8 Flash
Reflection Beam 1.0 is comparatively weak here — text-only input; some users report reasoning loops on long agent runs
501B-parameter sparse MoE (about 23B active per token) with weights on Hugging Face under Apache 2.0
Reflection Beam 1.0
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models — and its weights are open while Gemini 3.8 Flash is API-only.
Reflection claims 3-4x less inference compute than rival models (vendor claim)
Reflection Beam 1.0
Gemini 3.8 Flash is comparatively weak here — hLE-Verified score (54.9%) trails top frontier reasoning models
Fast and cheap to run: Artificial Analysis measured about 385 output tokens/sec and $0.12 per index task
Reflection Beam 1.0
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models — and it is the newer of the two.
Lowest cost at scale
Reflection Beam 1.0
Its weights are open, so at volume you pay for your own hardware instead of Gemini 3.8 Flash's $0.75/$3.75 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Reflection Beam 1.0
At Open weight (self-host / free) it undercuts Gemini 3.8 Flash, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ Reflection Beam 1.0
Open weights let you run it on your own hardware; Gemini 3.8 Flash is API-only.
Anyone whose priority is long-horizon agentic coding (deepswe v1.1)
→ Gemini 3.8 Flash
It is specifically built for that.
Anyone whose priority is 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0
→ Reflection Beam 1.0
That is its strongest area.
Gemini 3.8 Flash: where it fits
Google's cost-efficient workhorse model released September 2, 2026, tuned for long-horizon coding and autonomous agents, launched alongside a restricted 'Cyber' variant for vulnerability research. Released September 2, 2026 by Google DeepMind, it is built for long-horizon agentic coding (DeepSWE v1.1), cost-efficient workhorse performance beating larger models at same price as 3.7 Flash, vals Finance Agent V2 benchmark (61.4%, ahead of Claude Opus 5's 58.6%); also leads a weak field on the Harvey legal benchmark (10.0%), and prompt-injection robustness (Gray Swan benchmark).
Its trade-offs are real: still a mid-tier 'Flash' model, not Google's frontier flagship (which remains unreleased), introductory price doubles on January 1, 2027, hLE-Verified score (54.9%) trails top frontier reasoning models, and built on the same base model as Gemini 3.7 Flash (a post-training update, not a freshly pretrained model). At $0.75 in / $3.75 out per million tokens, it sits in the budget price band.
Reflection Beam 1.0: where it fits
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models. Released October 16, 2026 by Reflection AI, it is built for 501B-parameter sparse MoE (about 23B active per token) with weights on Hugging Face under Apache 2.0, reflection claims 3-4x less inference compute than rival models (vendor claim), fast and cheap to run: Artificial Analysis measured about 385 output tokens/sec and $0.12 per index task, and third-party hosts list it from $0.25/$1.00 per million tokens (Nebius, as of Oct 27); Reflection's own API is in free beta.
Its trade-offs: artificial Analysis Intelligence Index of 30, well below DeepSeek V4.1 Flash and GLM-5.3 (45), text-only input; some users report reasoning loops on long agent runs, self-hosting needs about 353 GB of GPU memory even at NVFP4, and kernels are CUDA-only for now, and headline benchmarks come from Reflection's own model card; independent evaluation was limited at launch. 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. Reflection Beam 1.0 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Gemini 3.8 Flash 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 Gemini 3.8 Flash and Reflection Beam 1.0 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.
See pricingFrequently asked questions
Is Gemini 3.8 Flash or Reflection Beam 1.0 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, Gemini 3.8 Flash leans toward long-horizon agentic coding (deepswe v1.1) while Reflection Beam 1.0 leans toward 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.8 Flash or Reflection Beam 1.0?
Reflection Beam 1.0 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 3.8 Flash is API-metered at $0.75/$3.75 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?
Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Gemini 3.8 Flash and Reflection Beam 1.0 together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.8 Flash, Reflection Beam 1.0 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, Gemini 3.8 Flash or Reflection Beam 1.0?
Reflection Beam 1.0 — released October 16, 2026, about 44 days after Gemini 3.8 Flash.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.