Pick North Mini Code for agentic software engineering, code generation, and terminal tasks or efficient sparse moe — 3b active of 30b, runs on a single h100. 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, North Mini Code is the value pick.
North Mini Code (Cohere, Canada) and Step 3.7 Flash (StepFun, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. North Mini Code is cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. 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. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: 256K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Ecosystem: this is a Canada-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
North Mini Code
Step 3.7 Flash
Provider
Cohere (Canada)
StepFun (China)
Released
June 9, 2026
May 29, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.2/$1.15 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
67.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Agentic software engineering, code generation, and terminal tasks: North Mini Code — Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100 — and it is the newer of the two.
Efficient sparse MoE — 3B active of 30B, runs on a single H100: North Mini Code — North Mini Code lists efficient sparse MoE — 3B active of 30B, runs on a single H100 among its strengths; Step 3.7 Flash does not.
High throughput (up to 2.8x Devstral Small 2) at low latency: North Mini Code — Step 3.7 Flash is comparatively weak here — smaller ecosystem and less third-party documentation than the more established Chinese labs
A 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows: Step 3.7 Flash — North Mini Code is comparatively weak here — text-only and coding-specialized — not multimodal or general-purpose
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; North Mini Code 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; North Mini Code does not.
Lowest cost at scale: North Mini Code — Its weights are open, so at volume you pay for your own hardware instead of Step 3.7 Flash's $0.2/$1.15 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: North Mini Code — At Open weight (self-host / free) it undercuts Step 3.7 Flash, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Step 3.7 Flash — Larger 256K window fits more in one prompt.
Anyone whose priority is agentic software engineering, code generation, and terminal tasks: North Mini Code — 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.
An enterprise with regional data-residency rules: Step 3.7 Flash or North Mini Code — Origin (Canada vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
North Mini Code: where it fits
Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. Released June 9, 2026 by Cohere, it is built for agentic software engineering, code generation, and terminal tasks, efficient sparse MoE — 3B active of 30B, runs on a single H100, high throughput (up to 2.8x Devstral Small 2) at low latency, and fully open weights under Apache 2.0 with fp8 and 4-bit builds.
Its trade-offs are real: text-only and coding-specialized — not multimodal or general-purpose, and 256K context and modest general-intelligence index trail frontier models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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
This is less "which is smarter" and more "which ecosystem fits." North Mini Code (Canada) and Step 3.7 Flash (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. North Mini Code is the cheaper option, which matters at volume. 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 North Mini Code or Step 3.7 Flash better for coding?
Public SWE-Bench figures are not available for Step 3.7 Flash, so the honest test is your own repository — run an identical real bug through both. By design, North Mini Code leans toward agentic software engineering, code generation, and terminal tasks 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, North Mini Code or Step 3.7 Flash?
North Mini Code is cheaper — Open weight (self-host / free) vs $0.2/$1.15 per 1M tokens.
Which has the bigger context window?
Effectively neither — 256K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both North Mini Code and Step 3.7 Flash together?
Yes — a multi-model platform like LumiChats gives you North Mini Code, 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, North Mini Code or Step 3.7 Flash?
North Mini Code — released June 9, 2026, about 11 days after Step 3.7 Flash.
North Mini Code vs Step 3.7 Flash
Cohere · Canada | StepFun · China · Updated June 2026
Quick verdict
Pick North Mini Code for agentic software engineering, code generation, and terminal tasks or efficient sparse moe — 3b active of 30b, runs on a single h100. 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, North Mini Code is the value pick.
North Mini Code (Cohere, Canada) and Step 3.7 Flash (StepFun, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. North Mini Code is cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. 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. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: 256K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Ecosystem: this is a Canada-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
North Mini Code
Step 3.7 Flash
Provider
Cohere (Canada)
StepFun (China)
Released
June 9, 2026
May 29, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.2/$1.15 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
67.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Agentic software engineering, code generation, and terminal tasks
North Mini Code
Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100 — and it is the newer of the two.
Efficient sparse MoE — 3B active of 30B, runs on a single H100
North Mini Code
North Mini Code lists efficient sparse MoE — 3B active of 30B, runs on a single H100 among its strengths; Step 3.7 Flash does not.
High throughput (up to 2.8x Devstral Small 2) at low latency
North Mini Code
Step 3.7 Flash is comparatively weak here — smaller ecosystem and less third-party documentation than the more established Chinese labs
A 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows
Step 3.7 Flash
North Mini Code is comparatively weak here — text-only and coding-specialized — not multimodal or general-purpose
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; North Mini Code 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; North Mini Code does not.
Lowest cost at scale
North Mini Code
Its weights are open, so at volume you pay for your own hardware instead of Step 3.7 Flash's $0.2/$1.15 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ North Mini Code
At Open weight (self-host / free) it undercuts Step 3.7 Flash, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Step 3.7 Flash
Larger 256K window fits more in one prompt.
Anyone whose priority is agentic software engineering, code generation, and terminal tasks
→ North Mini Code
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.
An enterprise with regional data-residency rules
→ Step 3.7 Flash or North Mini Code
Origin (Canada vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
North Mini Code: where it fits
Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. Released June 9, 2026 by Cohere, it is built for agentic software engineering, code generation, and terminal tasks, efficient sparse MoE — 3B active of 30B, runs on a single H100, high throughput (up to 2.8x Devstral Small 2) at low latency, and fully open weights under Apache 2.0 with fp8 and 4-bit builds.
Its trade-offs are real: text-only and coding-specialized — not multimodal or general-purpose, and 256K context and modest general-intelligence index trail frontier models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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
This is less "which is smarter" and more "which ecosystem fits." North Mini Code (Canada) and Step 3.7 Flash (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. North Mini Code is the cheaper option, which matters at volume. 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 North Mini Code 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 North Mini Code or Step 3.7 Flash better for coding?
Public SWE-Bench figures are not available for Step 3.7 Flash, so the honest test is your own repository — run an identical real bug through both. By design, North Mini Code leans toward agentic software engineering, code generation, and terminal tasks 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, North Mini Code or Step 3.7 Flash?
North Mini Code is cheaper — Open weight (self-host / free) vs $0.2/$1.15 per 1M tokens.
Which has the bigger context window?
Effectively neither — 256K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both North Mini Code and Step 3.7 Flash together?
Yes — a multi-model platform like LumiChats gives you North Mini Code, 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, North Mini Code or Step 3.7 Flash?
North Mini Code — released June 9, 2026, about 11 days 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.