Pick Qwen3 235B A22B (2507) for deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux) or exceptional multilingual and alignment results (79.2 arena-hard v2, 85.2 writingbench). 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.
Qwen3 235B A22B (2507) (Alibaba, China) and Reka Flash 3.1 (Reka AI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Qwen3 235B A22B (2507) is an older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. 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. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: Qwen3 235B A22B (2507) holds 8× more — 256K (~393 pages) vs 32K (~49 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Qwen3 235B A22B (2507) is the newer model by about 20 days (released July 21, 2025), usually meaning fresher training data and capabilities.
Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Qwen3 235B A22B (2507)
Reka Flash 3.1
Provider
Alibaba (China)
Reka AI (US)
Released
July 21, 2025
July 2025
Context window
256K (~393 pages)
32K (~49 pages)
Price (in/out)
Open weight (self-host / free)
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
Deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux): Qwen3 235B A22B (2507) — Reka Flash 3.1 is comparatively weak here — reka's broader roadmap has shifted toward robotics/world models after merging with Moonvalley in June 2026, raising questions about ongoing LLM investment
Exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench): Qwen3 235B A22B (2507) — An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding — and it carries the larger 256K context.
Outstanding structured logic — 95.0 on ZebraLogic: Qwen3 235B A22B (2507) — An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding — and it is the newer of the two.
A 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists): Reka Flash 3.1 — Qwen3 235B A22B (2507) is comparatively weak here — text-only with no vision, and the absence of a thinking mode caps its hardest reasoning
Strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3: Reka Flash 3.1 — Qwen3 235B A22B (2507) is comparatively weak here — coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on
Fully open weights (Apache 2.0) from a frontier-caliber research team: Reka Flash 3.1 — Qwen3 235B A22B (2507) is comparatively weak here — its 235B weights need roughly 438GB in BF16, far beyond consumer hardware
Largest single-prompt input: Qwen3 235B A22B (2507) — Its 256K window is about 8× larger than Reka Flash 3.1's 32K, fitting roughly 393 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases: Qwen3 235B A22B (2507) — Larger 256K window fits more in one prompt.
Anyone whose priority is deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux): Qwen3 235B A22B (2507) — 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.
An enterprise with regional data-residency rules: Reka Flash 3.1 or Qwen3 235B A22B (2507) — Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Qwen3 235B A22B (2507): where it fits
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. Released July 21, 2025 by Alibaba, it is built for deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux), exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench), outstanding structured logic — 95.0 on ZebraLogic, and no thinking mode, which makes latency and token spend entirely predictable.
Its trade-offs are real: nearly a year old and superseded — Artificial Analysis now steers users to Qwen3.5-397B instead, text-only with no vision, and the absence of a thinking mode caps its hardest reasoning, coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on, and its 235B weights need roughly 438GB in BF16, far beyond consumer hardware. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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
This is less "which is smarter" and more "which ecosystem fits." Qwen3 235B A22B (2507) (China) and Reka Flash 3.1 (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. 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 Qwen3 235B A22B (2507) 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, Qwen3 235B A22B (2507) leans toward deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux) 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, Qwen3 235B A22B (2507) or Reka Flash 3.1?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Qwen3 235B A22B (2507) — 256K vs 32K, about 8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Qwen3 235B A22B (2507) and Reka Flash 3.1 together?
Yes — a multi-model platform like LumiChats gives you Qwen3 235B A22B (2507), 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, Qwen3 235B A22B (2507) or Reka Flash 3.1?
Qwen3 235B A22B (2507) — released July 21, 2025, about 20 days after Reka Flash 3.1.
Qwen3 235B A22B (2507) vs Reka Flash 3.1
Alibaba · China | Reka AI · US · Updated June 2026
Quick verdict
Pick Qwen3 235B A22B (2507) for deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux) or exceptional multilingual and alignment results (79.2 arena-hard v2, 85.2 writingbench). 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.
Qwen3 235B A22B (2507) (Alibaba, China) and Reka Flash 3.1 (Reka AI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Qwen3 235B A22B (2507) is an older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. 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. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Context window: Qwen3 235B A22B (2507) holds 8× more — 256K (~393 pages) vs 32K (~49 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Qwen3 235B A22B (2507) is the newer model by about 20 days (released July 21, 2025), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Qwen3 235B A22B (2507)
Reka Flash 3.1
Provider
Alibaba (China)
Reka AI (US)
Released
July 21, 2025
July 2025
Context window
256K (~393 pages)
32K (~49 pages)
Price (in/out)
Open weight (self-host / free)
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
Deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux)
Qwen3 235B A22B (2507)
Reka Flash 3.1 is comparatively weak here — reka's broader roadmap has shifted toward robotics/world models after merging with Moonvalley in June 2026, raising questions about ongoing LLM investment
Exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench)
Qwen3 235B A22B (2507)
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding — and it carries the larger 256K context.
Outstanding structured logic — 95.0 on ZebraLogic
Qwen3 235B A22B (2507)
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding — and it is the newer of the two.
A 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists)
Reka Flash 3.1
Qwen3 235B A22B (2507) is comparatively weak here — text-only with no vision, and the absence of a thinking mode caps its hardest reasoning
Strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3
Reka Flash 3.1
Qwen3 235B A22B (2507) is comparatively weak here — coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on
Fully open weights (Apache 2.0) from a frontier-caliber research team
Reka Flash 3.1
Qwen3 235B A22B (2507) is comparatively weak here — its 235B weights need roughly 438GB in BF16, far beyond consumer hardware
Largest single-prompt input
Qwen3 235B A22B (2507)
Its 256K window is about 8× larger than Reka Flash 3.1's 32K, fitting roughly 393 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ Qwen3 235B A22B (2507)
Larger 256K window fits more in one prompt.
Anyone whose priority is deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux)
→ Qwen3 235B A22B (2507)
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.
An enterprise with regional data-residency rules
→ Reka Flash 3.1 or Qwen3 235B A22B (2507)
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Qwen3 235B A22B (2507): where it fits
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. Released July 21, 2025 by Alibaba, it is built for deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux), exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench), outstanding structured logic — 95.0 on ZebraLogic, and no thinking mode, which makes latency and token spend entirely predictable.
Its trade-offs are real: nearly a year old and superseded — Artificial Analysis now steers users to Qwen3.5-397B instead, text-only with no vision, and the absence of a thinking mode caps its hardest reasoning, coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on, and its 235B weights need roughly 438GB in BF16, far beyond consumer hardware. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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
This is less "which is smarter" and more "which ecosystem fits." Qwen3 235B A22B (2507) (China) and Reka Flash 3.1 (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. 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 Qwen3 235B A22B (2507) 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 Qwen3 235B A22B (2507) 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, Qwen3 235B A22B (2507) leans toward deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux) 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, Qwen3 235B A22B (2507) or Reka Flash 3.1?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Qwen3 235B A22B (2507) — 256K vs 32K, about 8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Qwen3 235B A22B (2507) and Reka Flash 3.1 together?
Yes — a multi-model platform like LumiChats gives you Qwen3 235B A22B (2507), 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, Qwen3 235B A22B (2507) or Reka Flash 3.1?
Qwen3 235B A22B (2507) — released July 21, 2025, about 20 days after Reka Flash 3.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.