Migrating off Qwen 3 32B
Qwen 3 32B (Groq) — retired 2026-07-17. Replaced by
Qwen 3.8 30B.
Source · Verified 2026-08-14.
Groq decommissioned Qwen 3 32B on 2026-07-17, the same day as Llama 4 Scout. Alibaba's own successor line (Qwen 3.6 27B, later 3.8 30B) is the direct migration path — this is one of the few retirements on this page with an unambiguous same-family replacement.
What should I use instead of Qwen 3 32B?
Qwen 3 32B, from Groq, was retired 2026-07-17. The recommended successor is Qwen 3.8 30B — swap the model id in your API calls and test side by side before cutting over production traffic.
The swap
// All AI Ask API
{
- "model": "qwen3-32b",
+ "model": "qwen3.8-30b",
"messages": [...]
}Same change applies if you call Groq directly with its own SDK — only the model identifier changes; request/response shape is otherwise unaffected for a same-provider swap.
What actually changes
| Qwen 3 32B | Qwen 3.8 30B |
|---|
| Blended $/M | — | $1.20 |
| Context window | 131,072 tokens | 131,072 tokens |
| Max output | 32,768 tokens | 32,768 tokens |
| Modalities | text | text, vision |
| Tokens / sec | unchanged / not measured | 690 |
Pricing from our live pricing registry; speed from our benchmark leaderboard where measured.
Gotchas
- Qwen 3.6 27B and 3.8 30B both add vision input that Qwen 3 32B never had — if you're sending image content expecting it to be ignored or stripped, verify your client isn't now accidentally billing for image tokens.
- The parameter count went down (32B → 30B) but real-world quality went up — Alibaba's newer training, not raw size, drives the improvement. Don't assume a smaller number means a downgrade here.
- Qwen 3.6 27B is itself already legacy (superseded by 3.8 30B) — if you're migrating anyway, going straight to 3.8 30B avoids doing this same exercise again shortly.
Alternatives beyond the obvious successor
Current Qwen flagship on Groq — skips the intermediate 3.6 27B step.
Larger open-weight alternative, also Groq-hosted, if you need more headroom.
Off Groq, similarly aggressive pricing for non-thinking workloads.
FAQ
Is Qwen 3 32B being shut down?
Yes — it was retired on 2026-07-17. Source: https://console.groq.com/docs/deprecations.
What should I switch to from Qwen 3 32B?
Qwen 3.8 30B is the direct successor. See "The swap" below for the exact model id change.
Will switching cost more or less?
See the pricing comparison table below for exact numbers.
Batch 50 · qwen3-32b decision and evidence contributions. Surface verification: 2026-08-14. These are route-local, server-rendered fixtures; unavailable values are not inferred.
Groq qwen-qwq-32b identity and thinking-mode resolver
Frozen Batch 50 fixture board. Formula / decision rule: resolved = groq host + qwen-qwq-32b endpoint + thinking-mode support + shutdown evidence Boundary: QwQ and Qwen3 are distinct model families; retirement of one does not retire the other.
| Frozen fixture / field ID | Joined inputs and observation | Calculated result | State |
|---|
batch50-qwen3-32b-m1-r1
qwen-qwq-32b on Groq · extended thinking mode | host=api.groq.com; endpoint=qwen-qwq-32b; thinking=budget_tokens param; shutdown=Unavailable per public docs 2026-08-14
Groq serves QwQ-32B with a budget_tokens thinking parameter; shutdown and successor are not documented publicly. | shutdown=Unavailable; check Groq console for exact date | UNAVAILABLE — console check required. |
batch50-qwen3-32b-m1-r2
Alibaba Cloud Model Studio Qwen3-32B · independent lifecycle | host=modelstudio.alibabacloud.com; endpoint=qwen3-32b; groq-notice=not-applicable; thinking=different param
Alibaba own Qwen3-32B has a separate deprecation policy and thinking parameter convention. | lifecycle=independent; do not apply Groq notice | PASS WITH SEPARATION — host-local. |
batch50-qwen3-32b-m1-r3
QwQ-32B vs Qwen3-32B family disambiguation | qwq=QwQ reasoning model; qwen3=Qwen3 instruction model; groq-deprecated=qwen-qwq-32b; qwen3-status=separate; confusion risk=string similarity
The two model families have different architectures and deprecation timelines. | verify which endpoint string is in use; do not cross-apply shutdown dates | VERIFY — family disambiguation required. |
Provenance: Batch 50 qwen3-32b module 1 first-party evidence, surface verification date 2026-08-14. Groq model deprecation notices. Missing joins fail closed.
Thinking-budget migration compatibility receipt
Frozen Batch 50 fixture board. Formula / decision rule: compatible = successor endpoint + budget_tokens param support + response schema match Boundary: Thinking-mode output format differs between providers; response parsing must be verified per successor.
| Frozen fixture / field ID | Joined inputs and observation | Calculated result | State |
|---|
batch50-qwen3-32b-m2-r1
budget_tokens parameter on successor · output format | old=qwen-qwq-32b; param=budget_tokens; successor=candidate; successor-param=Unavailable until verified; response=think block + answer
The thinking block format and budget_tokens support must be verified on the candidate successor. | param and format compatibility=Unavailable; verify per candidate | UNRESOLVED — successor param join required. |
batch50-qwen3-32b-m2-r2
Non-thinking mode fallback workload | old=qwen-qwq-32b; thinking=disabled; output=no think block; successor=any instruction model
In non-thinking mode, a broader set of successors is eligible since reasoning blocks are not required. | successor pool = instruction-class models; verify output schema only | FLEXIBLE — non-thinking migration. |
batch50-qwen3-32b-m2-r3
Downstream parser expecting thinking block delimiter | old=qwen-qwq-32b; parser=expects think delimiter; successor=no think block; parse failure=likely
Switching to a non-QwQ successor without a thinking block will break downstream parsers. | parser must be updated before migration; or successor must emit equivalent delimiter | FAIL CLOSED — parser update required. |
Provenance: Batch 50 qwen3-32b module 2 first-party evidence, surface verification date 2026-08-14. Qwen model hub release notes. Missing joins fail closed.
Cost-per-reasoning-token sensitivity table
Frozen Batch 50 fixture board. Formula / decision rule: reasoning cost = thinking_tokens x price_in + output_tokens x price_out Boundary: Thinking-token counts are model-controlled and workload-dependent; do not use as a billing forecast.
| Frozen fixture / field ID | Joined inputs and observation | Calculated result | State |
|---|
batch50-qwen3-32b-m3-r1
Short reasoning task · 1K thinking + 500 output | thinking=1000; output=500; qwq-price=approx $0.20/M; thinking-cost=0.0002; output-cost=0.0001; total=approx $0.0003
For short tasks, thinking token cost is manageable but scales with complexity. | estimated per-call cost = approx $0.0003 (indicative only; verify current pricing) | PASS — cost within expected range. |
batch50-qwen3-32b-m3-r2
Long reasoning task · 32K thinking + 2K output | thinking=32000; output=2000; qwq-price=approx $0.20/M; thinking-cost=0.0064; output-cost=0.0004; total=approx $0.0068
Long thinking chains significantly increase per-call cost; budget control needed. | set budget_tokens limit to cap thinking cost; measure before production | MONITOR — thinking budget required. |
batch50-qwen3-32b-m3-r3
Non-thinking mode · cost comparison to dense 70B | mode=non-thinking; output=2000; qwq-32b cost class=lower than 70B dense at Groq (indicative)
In non-thinking mode, QwQ-32B may be cheaper than a 70B dense model at Groq pricing. | verify current published pricing; cost class may shift post-deprecation | VERIFY — current pricing join required. |
Provenance: Batch 50 qwen3-32b module 3 first-party evidence, surface verification date 2026-08-14. Groq model deprecation notices. Missing joins fail closed.
Run the old prompt against both models, side by side
The only real way to know if a migration is safe is to test it. One workspace, both models, your actual prompts.
Try It Free