Pick Mistral Medium 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier or 128b dense open-weight model — self-hostable. 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, Step 3.7 Flash is the value pick.
Mistral Medium 3.5 (Mistral AI, France) 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. Mistral Medium 3.5 is mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). 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
Price: Step 3.7 Flash is about 7.5× cheaper on input ($0.2/$1.15 per 1M tokens vs $1.5/$7.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
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.
Recency: Step 3.7 Flash is the newer model by about 31 days (released May 29, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a France-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Mistral Medium 3.5
Step 3.7 Flash
Provider
Mistral AI (France)
StepFun (China)
Released
April 28, 2026
May 29, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
$1.5/$7.5 per 1M tokens
$0.2/$1.15 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier: Mistral Medium 3.5 — Mistral Medium 3.5 lists strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier among its strengths; Step 3.7 Flash does not.
128B dense open-weight model — self-hostable: Mistral Medium 3.5 — Mistral Medium 3.5 lists 128B dense open-weight model — self-hostable among its strengths; Step 3.7 Flash does not.
Unifies reasoning and coding into one model with an adjustable reasoning effort: Mistral Medium 3.5 — Mistral Medium 3.5 lists unifies reasoning and coding into one model with an adjustable reasoning effort among its strengths; Step 3.7 Flash does not.
A 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows: Step 3.7 Flash — StepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights — and it runs cheaper at $0.2/$1.15 per 1M tokens.
SCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size: Step 3.7 Flash — Mistral Medium 3.5 is comparatively weak here — output pricing ($7.50/M) is higher than the cheapest Chinese rivals
Open weights (Apache 2.0) at a low per-token price: Step 3.7 Flash — At $0.2/$1.15 per 1M tokens it undercuts Mistral Medium 3.5 ($1.5/$7.5 per 1M tokens), and that gap compounds at volume.
Lowest cost at scale: Step 3.7 Flash — At $0.2/$1.15 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: Step 3.7 Flash — At $0.2/$1.15 per 1M tokens it undercuts Mistral Medium 3.5, 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 strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier: Mistral Medium 3.5 — 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 Mistral Medium 3.5 — Origin (France vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Mistral Medium 3.5: where it fits
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). Released April 28, 2026 by Mistral AI, it is built for strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier, 128B dense open-weight model — self-hostable, unifies reasoning and coding into one model with an adjustable reasoning effort, and 256K context with text and image input.
Its trade-offs are real: below the absolute frontier — a value/efficiency pick, not a flagship-beater, output pricing ($7.50/M) is higher than the cheapest Chinese rivals, license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use, and no native video or audio. At $1.5 in / $7.5 out per million tokens, it sits in the mid 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
This is less "which is smarter" and more "which ecosystem fits." Mistral Medium 3.5 (France) and Step 3.7 Flash (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Step 3.7 Flash 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 Mistral Medium 3.5 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, Mistral Medium 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier 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, Mistral Medium 3.5 or Step 3.7 Flash?
Step 3.7 Flash is cheaper — $1.5/$7.5 per 1M tokens vs $0.2/$1.15 per 1M tokens, roughly 7.5× apart on input.
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 Mistral Medium 3.5 and Step 3.7 Flash together?
Yes — a multi-model platform like LumiChats gives you Mistral Medium 3.5, 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, Mistral Medium 3.5 or Step 3.7 Flash?
Step 3.7 Flash — released May 29, 2026, about 31 days after Mistral Medium 3.5.
Mistral Medium 3.5 vs Step 3.7 Flash
Mistral AI · France | StepFun · China · Updated June 2026
Quick verdict
Pick Mistral Medium 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier or 128b dense open-weight model — self-hostable. 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, Step 3.7 Flash is the value pick.
Mistral Medium 3.5 (Mistral AI, France) 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. Mistral Medium 3.5 is mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). 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
▸Price: Step 3.7 Flash is about 7.5× cheaper on input ($0.2/$1.15 per 1M tokens vs $1.5/$7.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸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.
▸Recency: Step 3.7 Flash is the newer model by about 31 days (released May 29, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a France-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Mistral Medium 3.5
Step 3.7 Flash
Provider
Mistral AI (France)
StepFun (China)
Released
April 28, 2026
May 29, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
$1.5/$7.5 per 1M tokens
$0.2/$1.15 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier
Mistral Medium 3.5
Mistral Medium 3.5 lists strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier among its strengths; Step 3.7 Flash does not.
128B dense open-weight model — self-hostable
Mistral Medium 3.5
Mistral Medium 3.5 lists 128B dense open-weight model — self-hostable among its strengths; Step 3.7 Flash does not.
Unifies reasoning and coding into one model with an adjustable reasoning effort
Mistral Medium 3.5
Mistral Medium 3.5 lists unifies reasoning and coding into one model with an adjustable reasoning effort among its strengths; Step 3.7 Flash does not.
A 198B-parameter sparse MoE vision-language model (11B active) built specifically for agentic coding and search workflows
Step 3.7 Flash
StepFun's 198B MoE vision-language model built for coding and search agents - a distinct Chinese lab with genuinely competitive open weights — and it runs cheaper at $0.2/$1.15 per 1M tokens.
SCMP reported it 'outshines larger rivals' from DeepSeek and Moonshot on some benchmarks despite its smaller active size
Step 3.7 Flash
Mistral Medium 3.5 is comparatively weak here — output pricing ($7.50/M) is higher than the cheapest Chinese rivals
Open weights (Apache 2.0) at a low per-token price
Step 3.7 Flash
At $0.2/$1.15 per 1M tokens it undercuts Mistral Medium 3.5 ($1.5/$7.5 per 1M tokens), and that gap compounds at volume.
Lowest cost at scale
Step 3.7 Flash
At $0.2/$1.15 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
→ Step 3.7 Flash
At $0.2/$1.15 per 1M tokens it undercuts Mistral Medium 3.5, 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 strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier
→ Mistral Medium 3.5
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 Mistral Medium 3.5
Origin (France vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Mistral Medium 3.5: where it fits
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). Released April 28, 2026 by Mistral AI, it is built for strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier, 128B dense open-weight model — self-hostable, unifies reasoning and coding into one model with an adjustable reasoning effort, and 256K context with text and image input.
Its trade-offs are real: below the absolute frontier — a value/efficiency pick, not a flagship-beater, output pricing ($7.50/M) is higher than the cheapest Chinese rivals, license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use, and no native video or audio. At $1.5 in / $7.5 out per million tokens, it sits in the mid 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
This is less "which is smarter" and more "which ecosystem fits." Mistral Medium 3.5 (France) and Step 3.7 Flash (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Step 3.7 Flash 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 Mistral Medium 3.5 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 Mistral Medium 3.5 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, Mistral Medium 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier 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, Mistral Medium 3.5 or Step 3.7 Flash?
Step 3.7 Flash is cheaper — $1.5/$7.5 per 1M tokens vs $0.2/$1.15 per 1M tokens, roughly 7.5× apart on input.
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 Mistral Medium 3.5 and Step 3.7 Flash together?
Yes — a multi-model platform like LumiChats gives you Mistral Medium 3.5, 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, Mistral Medium 3.5 or Step 3.7 Flash?
Step 3.7 Flash — released May 29, 2026, about 31 days after Mistral Medium 3.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.