Pick Qwen3.8-Flash-Next for swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4) or cost efficiency: ~1/9th the training cost of qwen3.7-plus, ~12x cheaper api than flagship qwen3.8-max. Pick Step 3.7 Flash for a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows or scmp reported it 'outshines larger rivals' from deepseek and moonshot on some benchmarks despite its smaller active size. On a tight budget at scale, Qwen3.8-Flash-Next is the value pick.
Qwen3.8-Flash-Next (Alibaba) and Step 3.7 Flash (StepFun) are two of the models people most often weigh against each other in 2026. Qwen3.8-Flash-Next is alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max. Step 3.7 Flash is stepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Price: nearly identical — $0.16/$0.47 per 1M tokens vs $0.2/$1.15 per 1M tokens. Cost will not be the deciding factor here.
Context window: both advertise 262K tokens natively (extensible to 1M with YaRN) (~393 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: Qwen3.8-Flash-Next is the newer model by about 3 months (released August 26, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Qwen3.8-Flash-Next
Step 3.7 Flash
Provider
Alibaba (China)
StepFun (China)
Released
August 26, 2026
May 29, 2026
Context window
262K tokens natively (extensible to 1M with YaRN) (~393 pages)
256K (~393 pages)
Price (in/out)
$0.16/$0.47 per 1M tokens
$0.2/$1.15 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, video
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
SWE-bench Pro (62.5, ahead of Claude Opus 4.6 Max's 53.4): Qwen3.8-Flash-Next — Step 3.7 Flash is comparatively weak here — benchmark 'outshines rivals' claims are from press coverage of specific tests, not a full independent leaderboard sweep
Cost efficiency: ~1/9th the training cost of Qwen3.7-Plus, ~12x cheaper API than flagship Qwen3.8-Max: Qwen3.8-Flash-Next — At $0.16/$0.47 per 1M tokens it undercuts Step 3.7 Flash ($0.2/$1.15 per 1M tokens), and that gap compounds at volume.
Vision-based agentic tasks (AndroidWorld: 84.5): Qwen3.8-Flash-Next — Alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max — and it runs cheaper at $0.16/$0.47 per 1M tokens.
A 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows: Step 3.7 Flash — Step 3.7 Flash lists a 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows among its strengths; Qwen3.8-Flash-Next does not.
SCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size: Step 3.7 Flash — Step 3.7 Flash lists sCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size among its strengths; Qwen3.8-Flash-Next does not.
Open weights (Apache 2.0) at a low per-token price: Step 3.7 Flash — Step 3.7 Flash lists open weights (Apache 2.0) at a low per-token price among its strengths; Qwen3.8-Flash-Next does not.
Lowest cost at scale: Qwen3.8-Flash-Next — At $0.16/$0.47 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume: Qwen3.8-Flash-Next — At $0.16/$0.47 per 1M tokens it undercuts Step 3.7 Flash, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4): Qwen3.8-Flash-Next — It is specifically built for that.
Anyone whose priority is a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows: Step 3.7 Flash — That is its strongest area.
Qwen3.8-Flash-Next: where it fits
Alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max. Released August 26, 2026 by Alibaba, it is built for sWE-bench Pro (62.5, ahead of Claude Opus 4.6 Max's 53.4), cost efficiency: ~1/9th the training cost of Qwen3.7-Plus, ~12x cheaper API than flagship Qwen3.8-Max, vision-based agentic tasks (AndroidWorld: 84.5), and previews Qwen4's hybrid gated-DeltaNet plus sparse-attention architecture.
Its trade-offs are real: trails Claude Opus 4.6 Max on Humanity's Last Exam (35.9 vs 40.0), lower OSWorld 2.0 binary success rate (19.4%), and an open-weight architecture preview rather than Alibaba's polished flagship product. At $0.16 in / $0.47 out per million tokens, it sits in the budget price band.
Step 3.7 Flash: where it fits
StepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights. Released May 29, 2026 by StepFun, it is built for a 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows, sCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size, open weights (Apache 2.0) at a low per-token price, and includes a 1.8B vision encoder for image understanding alongside text.
Its trade-offs: stepFun is a newer, less established lab than DeepSeek, Alibaba, or Moonshot, benchmark 'outshines rivals' claims are from press coverage of specific tests, not a full independent leaderboard sweep, and smaller ecosystem and less third-party documentation than the more established Chinese labs. At $0.2 in / $1.15 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Qwen3.8-Flash-Next and Step 3.7 Flash overlap enough that the right pick depends on your specific job. Qwen3.8-Flash-Next costs less per token; and each leads in its own area — Qwen3.8-Flash-Next for swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4), Step 3.7 Flash for a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Qwen3.8-Flash-Next or Step 3.7 Flash 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, Qwen3.8-Flash-Next leans toward swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4) while Step 3.7 Flash leans toward a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Qwen3.8-Flash-Next or Step 3.7 Flash?
Qwen3.8-Flash-Next is cheaper — $0.16/$0.47 per 1M tokens vs $0.2/$1.15 per 1M tokens, roughly 1.3× apart on input.
Which has the bigger context window?
Both advertise 262K tokens natively (extensible to 1M with YaRN) (~393 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Qwen3.8-Flash-Next and Step 3.7 Flash together?
Yes — a multi-model platform like LumiChats gives you Qwen3.8-Flash-Next, Step 3.7 Flash 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, Qwen3.8-Flash-Next or Step 3.7 Flash?
Qwen3.8-Flash-Next — released August 26, 2026, about 3 months after Step 3.7 Flash.
Qwen3.8-Flash-Next vs Step 3.7 Flash
Alibaba · China | StepFun · China · Updated June 2026
Quick verdict
Pick Qwen3.8-Flash-Next for swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4) or cost efficiency: ~1/9th the training cost of qwen3.7-plus, ~12x cheaper api than flagship qwen3.8-max. Pick Step 3.7 Flash for a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows or scmp reported it 'outshines larger rivals' from deepseek and moonshot on some benchmarks despite its smaller active size. On a tight budget at scale, Qwen3.8-Flash-Next is the value pick.
Qwen3.8-Flash-Next (Alibaba) and Step 3.7 Flash (StepFun) are two of the models people most often weigh against each other in 2026. Qwen3.8-Flash-Next is alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max. Step 3.7 Flash is stepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Price: nearly identical — $0.16/$0.47 per 1M tokens vs $0.2/$1.15 per 1M tokens. Cost will not be the deciding factor here.
▸Context window: both advertise 262K tokens natively (extensible to 1M with YaRN) (~393 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: Qwen3.8-Flash-Next is the newer model by about 3 months (released August 26, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Qwen3.8-Flash-Next
Step 3.7 Flash
Provider
Alibaba (China)
StepFun (China)
Released
August 26, 2026
May 29, 2026
Context window
262K tokens natively (extensible to 1M with YaRN) (~393 pages)
256K (~393 pages)
Price (in/out)
$0.16/$0.47 per 1M tokens
$0.2/$1.15 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, video
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
SWE-bench Pro (62.5, ahead of Claude Opus 4.6 Max's 53.4)
Qwen3.8-Flash-Next
Step 3.7 Flash is comparatively weak here — benchmark 'outshines rivals' claims are from press coverage of specific tests, not a full independent leaderboard sweep
Cost efficiency: ~1/9th the training cost of Qwen3.7-Plus, ~12x cheaper API than flagship Qwen3.8-Max
Qwen3.8-Flash-Next
At $0.16/$0.47 per 1M tokens it undercuts Step 3.7 Flash ($0.2/$1.15 per 1M tokens), and that gap compounds at volume.
Vision-based agentic tasks (AndroidWorld: 84.5)
Qwen3.8-Flash-Next
Alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max — and it runs cheaper at $0.16/$0.47 per 1M tokens.
A 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows
Step 3.7 Flash
Step 3.7 Flash lists a 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows among its strengths; Qwen3.8-Flash-Next does not.
SCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size
Step 3.7 Flash
Step 3.7 Flash lists sCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size among its strengths; Qwen3.8-Flash-Next does not.
Open weights (Apache 2.0) at a low per-token price
Step 3.7 Flash
Step 3.7 Flash lists open weights (Apache 2.0) at a low per-token price among its strengths; Qwen3.8-Flash-Next does not.
Lowest cost at scale
Qwen3.8-Flash-Next
At $0.16/$0.47 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen3.8-Flash-Next
At $0.16/$0.47 per 1M tokens it undercuts Step 3.7 Flash, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4)
→ Qwen3.8-Flash-Next
It is specifically built for that.
Anyone whose priority is a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows
→ Step 3.7 Flash
That is its strongest area.
Qwen3.8-Flash-Next: where it fits
Alibaba's open-weight preview of its next-generation Qwen4 hybrid-attention architecture, released August 26, 2026 as a 125B-parameter (6B active) MoE model priced roughly 12x below its own flagship Qwen3.8-Max. Released August 26, 2026 by Alibaba, it is built for sWE-bench Pro (62.5, ahead of Claude Opus 4.6 Max's 53.4), cost efficiency: ~1/9th the training cost of Qwen3.7-Plus, ~12x cheaper API than flagship Qwen3.8-Max, vision-based agentic tasks (AndroidWorld: 84.5), and previews Qwen4's hybrid gated-DeltaNet plus sparse-attention architecture.
Its trade-offs are real: trails Claude Opus 4.6 Max on Humanity's Last Exam (35.9 vs 40.0), lower OSWorld 2.0 binary success rate (19.4%), and an open-weight architecture preview rather than Alibaba's polished flagship product. At $0.16 in / $0.47 out per million tokens, it sits in the budget price band.
Step 3.7 Flash: where it fits
StepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights. Released May 29, 2026 by StepFun, it is built for a 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows, sCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size, open weights (Apache 2.0) at a low per-token price, and includes a 1.8B vision encoder for image understanding alongside text.
Its trade-offs: stepFun is a newer, less established lab than DeepSeek, Alibaba, or Moonshot, benchmark 'outshines rivals' claims are from press coverage of specific tests, not a full independent leaderboard sweep, and smaller ecosystem and less third-party documentation than the more established Chinese labs. At $0.2 in / $1.15 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Qwen3.8-Flash-Next and Step 3.7 Flash overlap enough that the right pick depends on your specific job. Qwen3.8-Flash-Next costs less per token; and each leads in its own area — Qwen3.8-Flash-Next for swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4), Step 3.7 Flash for a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Qwen3.8-Flash-Next and Step 3.7 Flash 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 Qwen3.8-Flash-Next or Step 3.7 Flash 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, Qwen3.8-Flash-Next leans toward swe-bench pro (62.5, ahead of claude opus 4.6 max's 53.4) while Step 3.7 Flash leans toward a 198b-parameter sparse moe vision-language model (11b active) built specifically for agentic coding and search workflows, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Qwen3.8-Flash-Next or Step 3.7 Flash?
Qwen3.8-Flash-Next is cheaper — $0.16/$0.47 per 1M tokens vs $0.2/$1.15 per 1M tokens, roughly 1.3× apart on input.
Which has the bigger context window?
Both advertise 262K tokens natively (extensible to 1M with YaRN) (~393 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Qwen3.8-Flash-Next and Step 3.7 Flash together?
Yes — a multi-model platform like LumiChats gives you Qwen3.8-Flash-Next, Step 3.7 Flash 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, Qwen3.8-Flash-Next or Step 3.7 Flash?
Qwen3.8-Flash-Next — released August 26, 2026, about 3 months after Step 3.7 Flash.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.