Pick Microsoft Phi-4 for strong reasoning for a small 14b open-weight model or mit-licensed — fully self-hostable at no per-token cost. Pick Reka Flash 3.1 for a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists) or strong base for fine-tuning agentic tasks - notably improved coding since the original flash 3. On a tight budget at scale, Reka Flash 3.1 is the value pick.
Microsoft Phi-4 (Microsoft) and Reka Flash 3.1 (Reka AI) are two of the models people most often weigh against each other in 2026. Microsoft Phi-4 is microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only. Reka Flash 3.1 is reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: Reka Flash 3.1 holds 2× more — 32K (~49 pages) vs 16K (~25 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Reka Flash 3.1 is the newer model by about 6 months (released July 2025), usually meaning fresher training data and capabilities.
Specifications
Spec
Microsoft Phi-4
Reka Flash 3.1
Provider
Microsoft (US)
Reka AI (US)
Released
January 10, 2025
July 2025
Context window
16K (~25 pages)
32K (~49 pages)
Price (in/out)
$0.07/$0.14 per 1M tokens
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong reasoning for a small 14B open-weight model: Microsoft Phi-4 — Reka Flash 3.1 is comparatively weak here — a relatively small 32K context window next to million-token frontier models
MIT-licensed — fully self-hostable at no per-token cost: Microsoft Phi-4 — Microsoft Phi-4 lists mIT-licensed — fully self-hostable at no per-token cost among its strengths; Reka Flash 3.1 does not.
Runs on modest or local hardware: Microsoft Phi-4 — Microsoft Phi-4 lists runs on modest or local hardware among its strengths; Reka Flash 3.1 does not.
A 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists): Reka Flash 3.1 — Microsoft Phi-4 is comparatively weak here — a tiny 16K context — by far the smallest window in this comparison
Strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3: Reka Flash 3.1 — Microsoft Phi-4 is comparatively weak here — an early-2025 small model, outclassed on hard tasks by 2026 flagships
Fully open weights (Apache 2.0) from a frontier-caliber research team: Reka Flash 3.1 — Reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni — and it carries the larger 32K context.
Lowest cost at scale: Reka Flash 3.1 — Its weights are open, so at volume you pay for your own hardware instead of Microsoft Phi-4's $0.07/$0.14 per 1M tokens.
Largest single-prompt input: Reka Flash 3.1 — Its 32K window is about 2× larger than Microsoft Phi-4's 16K, fitting roughly 49 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Reka Flash 3.1 — At Open weight (self-host / free) it undercuts Microsoft Phi-4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Reka Flash 3.1 — Larger 32K window fits more in one prompt.
Anyone whose priority is strong reasoning for a small 14b open-weight model: Microsoft Phi-4 — It is specifically built for that.
Anyone whose priority is a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists): Reka Flash 3.1 — That is its strongest area.
Microsoft Phi-4: where it fits
Microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only. Released January 10, 2025 by Microsoft, it is built for strong reasoning for a small 14B open-weight model, mIT-licensed — fully self-hostable at no per-token cost, runs on modest or local hardware, and very cheap hosted inference at about $0.07/$0.14.
Its trade-offs are real: a tiny 16K context — by far the smallest window in this comparison, text only — no image, audio or video input, an early-2025 small model, outclassed on hard tasks by 2026 flagships, and no first-party per-token API; hosted prices are third-party. At $0.07 in / $0.14 out per million tokens, it sits in the budget price band.
Reka Flash 3.1: where it fits
Reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni. Released July 2025 by Reka AI, it is built for a 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists), strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3, fully open weights (Apache 2.0) from a frontier-caliber research team, and built by alumni from Google DeepMind and Meta's AI labs.
Its trade-offs: a relatively small 32K context window next to million-token frontier models, smaller and less capable overall than flagship frontier models from major labs, and reka's broader roadmap has shifted toward robotics/world models after merging with Moonvalley in June 2026, raising questions about ongoing LLM investment. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Microsoft Phi-4 and Reka Flash 3.1 overlap enough that the right pick depends on your specific job. Reka Flash 3.1 costs less per token; Reka Flash 3.1 holds the larger context; and each leads in its own area — Microsoft Phi-4 for strong reasoning for a small 14b open-weight model, Reka Flash 3.1 for a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Microsoft Phi-4 or Reka Flash 3.1 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, Microsoft Phi-4 leans toward strong reasoning for a small 14b open-weight model while Reka Flash 3.1 leans toward a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Microsoft Phi-4 or Reka Flash 3.1?
Reka Flash 3.1 is cheaper — $0.07/$0.14 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
Reka Flash 3.1 — 32K vs 16K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Microsoft Phi-4 and Reka Flash 3.1 together?
Yes — a multi-model platform like LumiChats gives you Microsoft Phi-4, Reka Flash 3.1 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, Microsoft Phi-4 or Reka Flash 3.1?
Reka Flash 3.1 — released July 2025, about 6 months after Microsoft Phi-4.
Microsoft Phi-4 vs Reka Flash 3.1
Microsoft · US | Reka AI · US · Updated June 2026
Quick verdict
Pick Microsoft Phi-4 for strong reasoning for a small 14b open-weight model or mit-licensed — fully self-hostable at no per-token cost. Pick Reka Flash 3.1 for a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists) or strong base for fine-tuning agentic tasks - notably improved coding since the original flash 3. On a tight budget at scale, Reka Flash 3.1 is the value pick.
Microsoft Phi-4 (Microsoft) and Reka Flash 3.1 (Reka AI) are two of the models people most often weigh against each other in 2026. Microsoft Phi-4 is microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only. Reka Flash 3.1 is reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: Reka Flash 3.1 holds 2× more — 32K (~49 pages) vs 16K (~25 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Reka Flash 3.1 is the newer model by about 6 months (released July 2025), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Microsoft Phi-4
Reka Flash 3.1
Provider
Microsoft (US)
Reka AI (US)
Released
January 10, 2025
July 2025
Context window
16K (~25 pages)
32K (~49 pages)
Price (in/out)
$0.07/$0.14 per 1M tokens
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong reasoning for a small 14B open-weight model
Microsoft Phi-4
Reka Flash 3.1 is comparatively weak here — a relatively small 32K context window next to million-token frontier models
MIT-licensed — fully self-hostable at no per-token cost
Microsoft Phi-4
Microsoft Phi-4 lists mIT-licensed — fully self-hostable at no per-token cost among its strengths; Reka Flash 3.1 does not.
Runs on modest or local hardware
Microsoft Phi-4
Microsoft Phi-4 lists runs on modest or local hardware among its strengths; Reka Flash 3.1 does not.
A 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists)
Reka Flash 3.1
Microsoft Phi-4 is comparatively weak here — a tiny 16K context — by far the smallest window in this comparison
Strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3
Reka Flash 3.1
Microsoft Phi-4 is comparatively weak here — an early-2025 small model, outclassed on hard tasks by 2026 flagships
Fully open weights (Apache 2.0) from a frontier-caliber research team
Reka Flash 3.1
Reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni — and it carries the larger 32K context.
Lowest cost at scale
Reka Flash 3.1
Its weights are open, so at volume you pay for your own hardware instead of Microsoft Phi-4's $0.07/$0.14 per 1M tokens.
Largest single-prompt input
Reka Flash 3.1
Its 32K window is about 2× larger than Microsoft Phi-4's 16K, fitting roughly 49 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Reka Flash 3.1
At Open weight (self-host / free) it undercuts Microsoft Phi-4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Reka Flash 3.1
Larger 32K window fits more in one prompt.
Anyone whose priority is strong reasoning for a small 14b open-weight model
→ Microsoft Phi-4
It is specifically built for that.
Anyone whose priority is a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists)
→ Reka Flash 3.1
That is its strongest area.
Microsoft Phi-4: where it fits
Microsoft's MIT-licensed 14B open model — strong reasoning for its size and very cheap, but a tiny 16K context and text-only. Released January 10, 2025 by Microsoft, it is built for strong reasoning for a small 14B open-weight model, mIT-licensed — fully self-hostable at no per-token cost, runs on modest or local hardware, and very cheap hosted inference at about $0.07/$0.14.
Its trade-offs are real: a tiny 16K context — by far the smallest window in this comparison, text only — no image, audio or video input, an early-2025 small model, outclassed on hard tasks by 2026 flagships, and no first-party per-token API; hosted prices are third-party. At $0.07 in / $0.14 out per million tokens, it sits in the budget price band.
Reka Flash 3.1: where it fits
Reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni. Released July 2025 by Reka AI, it is built for a 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists), strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3, fully open weights (Apache 2.0) from a frontier-caliber research team, and built by alumni from Google DeepMind and Meta's AI labs.
Its trade-offs: a relatively small 32K context window next to million-token frontier models, smaller and less capable overall than flagship frontier models from major labs, and reka's broader roadmap has shifted toward robotics/world models after merging with Moonvalley in June 2026, raising questions about ongoing LLM investment. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Microsoft Phi-4 and Reka Flash 3.1 overlap enough that the right pick depends on your specific job. Reka Flash 3.1 costs less per token; Reka Flash 3.1 holds the larger context; and each leads in its own area — Microsoft Phi-4 for strong reasoning for a small 14b open-weight model, Reka Flash 3.1 for a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Microsoft Phi-4 and Reka Flash 3.1 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 Microsoft Phi-4 or Reka Flash 3.1 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, Microsoft Phi-4 leans toward strong reasoning for a small 14b open-weight model while Reka Flash 3.1 leans toward a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Microsoft Phi-4 or Reka Flash 3.1?
Reka Flash 3.1 is cheaper — $0.07/$0.14 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
Reka Flash 3.1 — 32K vs 16K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Microsoft Phi-4 and Reka Flash 3.1 together?
Yes — a multi-model platform like LumiChats gives you Microsoft Phi-4, Reka Flash 3.1 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, Microsoft Phi-4 or Reka Flash 3.1?
Reka Flash 3.1 — released July 2025, about 6 months after Microsoft Phi-4.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.