Qwen3 Coder Next API model profile
Evidence snapshot:
Qwen3 Coder Next is a Alibaba Qwen model profile with a 262,144-token context window. The dated catalog snapshot records text modalities and interfaces for agentic, coding, prompt caching, reasoning, structured output.
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...
Qwen3 Coder Next is mid-catalog on every dimension this snapshot measures. Pick it when it is already in your stack or when the specifics below match the job, not because a number here stands out.
Qwen3 Coder Next is available under the Kendr alias kc-qwen3-coder-next. Current account availability and customer credit quotes come from Kendr's live public model API and applicable account policy.
Qwen3 Coder Next accepts text and returns text. The snapshot records agentic, coding, prompt caching, reasoning, structured output, text generation, tool calling, tools, and web search as capabilities or interfaces.
The dated reference snapshot lists $0.12 input and $0.8 output per million tokens. Cached input is $0.036 per million tokens. The separately published provider-route reference is Route-specific (From $0.30 / $1.20 depending on the selected route; up to $0.50 / $1.50).
The 2026-09-06 snapshot includes 1 Artificial Analysis index. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.
No comparable popularity rank or traffic share is present in the 2026-09-06 snapshot. No comparable routing rank or traffic-share observation is attached to this dated profile; missing adoption evidence is not estimated.
Profile data was reviewed for the 2026-09-06 snapshot. Claims retain their source dates, and unavailable fields are shown as unavailable instead of estimated.
Profile facts
- Profile type
- Kendr API model
- Kendr API alias
- kc-qwen3-coder-next
- Model developer
- Alibaba Qwen
- Kendr route provider
- Alibaba Qwen
- Context window
- 262K
- Snapshot date
- 2026-09-06
- Knowledge cutoff
- Not disclosed
- Reference catalog ID
- qwen/qwen3-coder-next
When to pick Qwen3 Coder Next
Qwen3 Coder Next is mid-catalog on every dimension this snapshot measures. Pick it when it is already in your stack or when the specifics below match the job, not because a number here stands out.
Each condition below is derived from this model's own values in the 2026-09-06 snapshot, compared only against models publishing the same field.
- Reach for it when the model has to call tools. Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
Context, modalities, and identity
Qwen3 Coder Next accepts text and returns text. The snapshot records agentic, coding, prompt caching, reasoning, structured output, text generation, tool calling, tools, and web search as capabilities or interfaces.
- Model developer
- Alibaba Qwen
- Kendr route provider
- Alibaba Qwen
- Context window
- 262K
- Maximum output
- 235,929 tokens
- Input modalities
- text
- Output modalities
- text
- Knowledge cutoff
- Not disclosed
Model overview
Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...
- Reference model ID
- qwen/qwen3-coder-next
- Canonical version
- qwen/qwen3-coder-next-2025-02-03
- Hugging Face ID
- Qwen/Qwen3-Coder-Next
Capabilities and supported controls
Capabilities and parameters are reported from the dated catalog and source records; their presence does not guarantee identical behavior across every provider route.
- Supported parameters
- frequency_penalty, logit_bias, logprobs, max_tokens, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p
- agentic
- coding
- prompt caching
- reasoning
- structured output
- text generation
- tool calling
- tools
- web search
Dated pricing snapshot
The dated reference snapshot lists $0.12 input and $0.8 output per million tokens. Cached input is $0.036 per million tokens. The separately published provider-route reference is Route-specific (From $0.30 / $1.20 depending on the selected route; up to $0.50 / $1.50).
Reference figures are dated 2026-09-06; the live Kendr quote can differ by selected provider route, context tier, caching, tools, region, and current rate card.
- Price date
- 2026-09-06
- Input
- $0.12 per 1M tokens
- Cached input
- $0.036 per 1M tokens
- Output
- $0.8 per 1M tokens
Provider routes, performance, and uptime
The snapshot retains 4 provider endpoints. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.
- Active provider endpoints
- 4
- Best p50 latency
- No recent metric
- Best p50 throughput
- No recent metric
- Availability with routing
- No recent metric
- Availability without routing
- No recent metric
- Performance date
- 2026-09-06
| Provider | Quantization | Input / 1M | Output / 1M | Cache read / 1M | Context | p50 latency | p50 throughput | Uptime (1d) |
|---|---|---|---|---|---|---|---|---|
| Parasail | bf16 | $0.12 / 1M | $0.8 / 1M | $0.07 / 1M | 262,144 tokens | No recent p50 | No recent p50 | 99.98% |
| StreamLake | unknown | $0.18 / 1M | $0.9 / 1M | $0.036 / 1M | 256,000 tokens | No recent p50 | No recent p50 | 99.25% |
| Novita | fp8 | $0.2 / 1M | $1.5 / 1M | No verified rate | 262,144 tokens | No recent p50 | No recent p50 | 99.14% |
| Alibaba | unknown | $0.3 / 1M | $1.5 / 1M | No verified rate | 262,144 tokens | No recent p50 | No recent p50 | 99.11% |
Benchmark evidence and limitations
The 2026-09-06 snapshot includes 1 Artificial Analysis index. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.
Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.
- Coding Index
- 36.2
Popularity and market context
No comparable popularity rank or traffic share is present in the 2026-09-06 snapshot. No comparable routing rank or traffic-share observation is attached to this dated profile; missing adoption evidence is not estimated.
- Third-party catalog rank
- No verified rank
- Global market share
- Not inferred
- Observation date
- 2026-09-06
OpenAI-compatible API example
This example applies to the published Kendr alias on this hosted profile. Check the live public catalog before use.
curl https://api.kendr.org/v1/chat/completions \
-H "Authorization: Bearer $KENDR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"kc-qwen3-coder-next","messages":[{"role":"user","content":"Hello"}]}'Frequently asked questions
When should I use Qwen3 Coder Next?
Qwen3 Coder Next is mid-catalog on every dimension this snapshot measures. Pick it when it is already in your stack or when the specifics below match the job, not because a number here stands out. Reach for it when the model has to call tools: Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
What is Qwen3 Coder Next?
Qwen3 Coder Next is a Alibaba Qwen model profile with a 262,144-token context window. The dated catalog snapshot records text modalities and interfaces for agentic, coding, prompt caching, reasoning, structured output.
What context window does Qwen3 Coder Next have?
The dated profile lists 262K of context and up to 235,929 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.
What benchmark evidence is available for Qwen3 Coder Next?
The 2026-09-06 snapshot includes 1 Artificial Analysis index. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable. Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.
What is the Kendr API alias for Qwen3 Coder Next?
Use kc-qwen3-coder-next as the model value. The live public model API and signed-in catalog remain authoritative for route availability and customer credit quotes.
How is Qwen3 Coder Next priced on Kendr?
The dated reference snapshot lists $0.12 input and $0.8 output per million tokens. Cached input is $0.036 per million tokens. The separately published provider-route reference is Route-specific (From $0.30 / $1.20 depending on the selected route; up to $0.50 / $1.50). Kendr applies one 5% markup to configured provider model cost; the live quote and settled routing receipt are authoritative for a request.
Sources and evidence dates
- Qwen3 Coder Next third-party catalog record (catalog, checked 2026-09-06)
- Third-party model catalog methodology (methodology, checked 2026-09-06)
- Alibaba Qwen official model documentation (primary, checked 2026-09-06)
- Artificial Analysis capability indices methodology (benchmark, checked 2026-09-06)
- Qwen3 Coder Next provider or route reference (primary, checked 2026-09-06)