GPT-5.4 vs Ling-2.6-Flash
GPT-5.4 (2026) and Ling-2.6-Flash (2026) are frontier reasoning models from OpenAI and InclusionAI. GPT-5.4 ships a 1.05m-token context window, while Ling-2.6-Flash ships a 262k-token context window. On pricing, GPT-5.4 ranges from $2.50 to $5/1M input tokens by tier; Ling-2.6-Flash costs $0.01/1M input tokens. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GPT-5.4 fits 4x more tokens; pick it for long-context work and Ling-2.6-Flash for tighter calls.
Decision scorecard
Local evidence first| Signal | GPT-5.4 | Ling-2.6-Flash |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | tool-calling agents and provider-routed production |
| Decision fit | Coding, RAG, and Agents | RAG, Agents, and Long context |
| Context window | 1.05m | 262k |
| Cheapest output | $15/1M tokens | $0.03/1M tokens |
| Provider routes | 4 tracked | 2 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- GPT-5.4 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.4 has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5.4 uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags GPT-5.4 for Coding, RAG, and Agents.
- Ling-2.6-Flash has the lower cheapest tracked output price at $0.03/1M tokens.
- Local decision data tags Ling-2.6-Flash for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5.4
$5,750
Cheapest tracked route/tier: OpenAI API
Ling-2.6-Flash
$15.50
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $5,735. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Ling-2.6-Flash is $14.97/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-5.4 is $14.97/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.4 adds Vision, Multimodal, and Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-05 | 2026-04-21 |
| Context window | 1.05m | 262k |
| Parameters | — | 104B (7.4B activated) |
| Architecture | Decoder Only | Mixture of Experts |
| License | Proprietary | Apache 2.0OSI-approved |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| Pricing attribute | GPT-5.4 | Ling-2.6-Flash |
|---|---|---|
| Input price |
| $0.01/1M tokens |
| Output price |
| $0.03/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.4 | Ling-2.6-Flash |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Deep dive
The capability footprint differs most on vision: GPT-5.4, multimodal input: GPT-5.4, reasoning mode: GPT-5.4, and code execution: GPT-5.4. Both models share function calling, tool use, and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, GPT-5.4 lists tiered pricing: 0-272,000t is $2.50/1M input and $15/1M output; 272,000t+ is $5/1M input and $22.50/1M output, while Ling-2.6-Flash lists $0.01/1M input and $0.03/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Ling-2.6-Flash lower by about $6.23 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 4 providers versus 2, so concentration risk also matters.
Choose GPT-5.4 when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Ling-2.6-Flash when provider fit and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, GPT-5.4 or Ling-2.6-Flash?
GPT-5.4 supports 1.05m tokens, while Ling-2.6-Flash supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, GPT-5.4 or Ling-2.6-Flash?
GPT-5.4 lists tiered pricing: 0-272,000t is $2.50/1M input and $15/1M output; 272,000t+ is $5/1M input and $22.50/1M output. Ling-2.6-Flash lists $0.01/1M input and $0.03/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.4 or Ling-2.6-Flash open source?
GPT-5.4 is listed under Proprietary. Ling-2.6-Flash is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, GPT-5.4 or Ling-2.6-Flash?
GPT-5.4 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, GPT-5.4 or Ling-2.6-Flash?
GPT-5.4 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-5.4 and Ling-2.6-Flash?
GPT-5.4 is available on OpenAI API, OpenRouter, Vercel AI Gateway, and AWS Bedrock. Ling-2.6-Flash is available on OpenRouter and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.